Self-Assembly of Short Peptide Derivatives

1

Self-Assembly of Short Peptide Derivatives

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

By

Tao Lin

Graduate Program in Chemistry

The Ohio State University

2021

Dissertation Committee

Professor Jonathan R. Parquette, Advisor

Professor Jovica D. Badjic

Professor Psaras L. McGrier

Professor Dale Hoyt

2

Copyrighted by

Tao Lin

2021

ii

Abstract

The self-assembly of simple peptides and peptide derivatives are powerful method

in developing new nanomaterials for tissue engineering, targeted drug delivery,

optoelectronics, etc. Many of the self-assembly system comprise only one component and

designing and controlling multicomponent self-assembly is challenging since not only

force balance between individual components but also noncovalent interactions between

different component should be included in the study. Here, we investigated self-assembly

consist of peptide and protein and multicomponent self-assembly of different peptides.

We synthesized a series of peptide derivatives AAC1-7 which contained amino

acids with different charges and antioxidative moieties. The self-assembly of the peptide

derivatives were investigated. Among the all the AACs, AAC2 displayed low cytotoxicity

and the co-assembly of AAC2 and human insulin was studied. Further studies revealed that

AAC2 itself had promising effect on controlling glucose homeostasis in vitro. Animal

studies in type 1 diabetic mice revealed that AAC2 maintained glucose homeostasis as

insulin without increasing adiposity. AAC2 also increased brain mass and anxiety-related

behaviors in type 1 diabetic mice. Overall, AAC2 induced glucose uptake via a distinct

mechanism that activated LepR/PKCς/GLUT1 axis and it could provide a novel strategy

to treat diabetes and prevent complications of nervous and insulin-resistant tissues.

iii

We also investigated multicomponent assembly of two oppositely charged

peptides. Positively charged peptide Fmoc-KK-BA (AAC7) and negatively charged

peptide Fmoc-EK-MC (AAC4’) were able to individually self-assemble into nanotubes and

nanofibers respectively. The self-assembly of both peptides were concentration dependent.

As pre-assembled AAC7 and AAC4’ were combined, electrostatic interactions between

positively charge AAC7 nanotubes and negatively charged AAC4’ nanofibers led to

wrapping of nanofibers on the surface of nanotubes. In contrast, when AAC7 and AAC4’

were combined in monomeric form, the co-assembly of the peptides resulted in nanofibers

with width of 13 nm, which were distinctive compare to the mixture of pre-assembled

peptides.

iv

Dedication

This document is dedicated to my parents Yongshuang Lin and Dajuan Yang, and

to my family and friends.

v

Acknowledgments

I would like to thank my advisor Dr. Jon R. Parquette for his guidance and support.

He is always patient and keen to help me out with my research. He would also encourage

me to explore new field in chemistry and I learned a lot in the past five years working with

him.

I would also like to thank all group members in Parquette lab for making the

working environment enjoyable and fun. I would like to express my sincere thanks to Dr.

Cassidy Creemer for helping me in the lab and inspiring me in the past five years. I want

to thank Dr. Yuan Sun, Dr. Mengmeng Liu and Dr. Aileen Shieh for teaching me lab skills

and giving me advise on my lab work when I started working in Parquette group. I also

want to thank Alessandro Brunetti for his help in the lab.

I would like to thank our collaborators Dr. Ouliana Ziouzenkova and Dr. Aejin Lee

in Ohio State University for teaching me knowledge in the field of human nutrition. I want

to also express my appreciation to Dr. Noel Paul for his support and help to me when I was

a graduate teaching assistant.

I would like to specifically thank my parents Yongshuang Lin and Dajuan Yang,

for always encouraging me to pursue my goals and supporting me in my life.

vi

Vita

2015................................................................B.S. Biochemistry, Department of Chemistry

and Biochemistry, The Ohio State University

2015 to present ..............................................Graduate Teaching Assistant, Department of

Chemistry and Biochemistry, The Ohio State

University

Publications

Petrov, B.; Aldoori, A.; James, C.; Yang, K.; Perez Algorta, G.; Lee, A.; Zhang, L.;

Lin, T.; Al Awadhi, R.; Parquette, J. R.; Samogyi, A.; Arnold, L. E.; Fristad, M. A.;

Gracious, B.; Ziouzenkova, O., Bipolar disorder in youth is associated with increased

levels of vitamin D-binding protein. Transl. Psychiatry 2018, 8: 61.

vii

Lee, A.; Sun, Y.; Lin, T.; Song, N.-J.; Mason, M. L.; Leung, J. H.; Kowdley, D.;

Wall, J.; Brunetti, A.; Fitzgerald, J.; Baer, L. A.; Stanford, K. I.; Ortega-Anaya, J.;

Gomes-Dias, L.; Needleman, B.; Noria, S.; Weil, Z.; Blakeslee, J. J.; Jiménez-Flores,

R.; Parquette, J. R.; Ziouzenkova, O., Amino acid-based compound activates atypical

PKC and leptin receptor pathways to improve glycemia and anxiety like behavior in

diabetic mice. Biomaterials 2020, 239, 119839.

Fields of Study

Major Field: Chemistry

viii

Table of Contents

Abstract ............................................................................................................................... ii

Dedication .......................................................................................................................... iv

Acknowledgments............................................................................................................... v

Vita ..................................................................................................................................... vi

List of Schemes ................................................................................................................... x

List of Figures .................................................................................................................... xi

List of Abbriviations ......................................................................................................... xx

Chapter 1 Peptide Self-assembly in Aqueous Medium ...................................................... 1

1.1 Introduction ............................................................................................................... 1

1.2 Significance of Water ............................................................................................... 2

1.3 Non-Covalent Interactions of Self-assembly in Water ............................................. 2

1.4 Assemblies of Peptides and Peptide Derivatives in Water ....................................... 6

1.5 References ............................................................................................................... 29

Chapter 2 Self-assembled Anti-diabetic Amino Acid Compound .................................... 36

2.1 Introduction ............................................................................................................. 36

ix

2.2 Results and Discussion ........................................................................................... 44

2.3 Experimental Section .............................................................................................. 66

2.4 References ............................................................................................................... 87

Chapter 3 Co-assembly of Two Oppositely Charged Peptides ......................................... 93

3.1 Introduction ............................................................................................................. 93

3.2 Results and Discussion ......................................................................................... 101

3.3 Experimental Section ............................................................................................ 129

3.4 References ............................................................................................................. 135

Bibliography ................................................................................................................... 138

Appendix A: NMR spectrum .......................................................................................... 154

x

List of Schemes

Scheme 1.1 Structures of Fmoc-dipeptide 1-7. ................................................................. 25

Scheme 2.1 Chemical structures and features of AAC1-7. .............................................. 45

Scheme 2.2 Synthesis of benzyl succinic acid. ................................................................. 67

Scheme 2.3 Synthesis of DAC. ......................................................................................... 67

Scheme 2.4 Synthesis of AAC1. ....................................................................................... 68






Scheme 2.10 Synthesis of AAC7. ..................................................................................... 74

Scheme 3.1 Synthesis of MC .......................................................................................... 130

Scheme 3.2 Synthesis of AAC7 ...................................................................................... 131

Scheme 3.3 Synthesis of AAC4’ .................................................................................... 132

xi

List of Figures

Figure 1.1 Self-assembled structures in nature. .................................................................. 2

Figure 1.2 Two typical π - π interaction: parallel-displaced and T-shaped. ....................... 5

Figure 1.3 Three components of van der Waals forces. Copyright 2017 Elsevier Inc.40 ... 5

Figure 1.4 Tubular structures formed from self-assembly of cyclic peptide. Copyright 1996

American Chemical Society.54 ............................................................................................ 8

Figure 1.5 Hierarchical assembly to hollow macrotubes. Copyright 2004 WILEY‐VCH

Verlag GmbH & Co. KGaA, Weinheim.58 ......................................................................... 9

Figure 1.6 Dipeptide NH2-Phe-Phe-COOH and its self-assembled nanotubes. Copyright

2003, American Association for the Advancement of Science.62 ..................................... 11

Figure 1.7 Tripeptide sequences; hydrogels and nanostructures formed by DVFF and DFFV.

Copyright 2012, The Royal Society of Chemistry.70 ........................................................ 12

Figure 1.8 Self-assemblies of FEFEFKFK at pH 2.8, 4 and 10. Copyright 2013, The Royal

Society of Chemistry.78 ..................................................................................................... 15

Figure 1.9 A. Chemical structure of the peptide amphiphile. B. Molecular model of the

PA. C. self-assembly of PA molecules into a cylindrical micelle. Copyright 2001, The

American Association for the Advancement of Science.84 ............................................... 18

Figure 1.10 A. Chemical structures of peptide amphiphile KLAK PA and pegylated

amphiphile PEG PA. Cryo-TEM of KLAK PA alone (B). KLAK with PEG (D) shows a

xii

significant difference in average length. Conventional TEM images show fiber formation

for both KLAK alone (C) and KLAK PA with PEG PA (E). Copyright 2012 American

Chemical Society.90........................................................................................................... 21

Figure 1.11 (a) The peptide amphiphile used for the polarization-sensitive polymerization

experiments. (b) The polymerization that occurs upon illumination of a diacetylene. (c)

Dependent on the polarization direction of the light (the arrows), one or the other

orientation of the fibers will polymerize. The darkness of the lines depicts their degree of

polymerization. A black line is fully polymerized, and light gray is nonpolymerized.

Copyright 2009 American Chemical Society.95................................................................ 23

Figure 1.12 Example of aromatic peptide derivatives. Copyright 2014 The Royal Society

of Chemistry.17 .................................................................................................................. 24

Figure 1.13 TEM images and actual samples of Fmoc-FG, Fmoc-GG and Fmoc-GF.

Copyright 2011 American Chemical Society.104 .............................................................. 26

Figure 1.14 TEM of evolution of structures with time for dipeptide in the presence of GdL

(14.42 mg/mL): (a) immediately after GdL addition; (b) 40 min, (c) 80 min, (d) 120 min,

(e) 160 min, (f) 200 min, (g) 240 min, (h) 280 min, and (i) 400 min after GdL addition. In

all cases, the scale bar represents 200 nm. Copyright 2009 American Chemical Society.109

........................................................................................................................................... 28

Figure 2.1 Two different insulin-releasing nanoparticles. Copyright 2014, Nature

Publishing Group, a division of Macmillan Publishers Limited.27 ................................... 39

Figure 2.2 A) Schematic of the enzyme-based glucose-responsive nanovesicle. B) The

chemical structure of the pH-sensitive polymer PEG-poly(Ser-Ketal), which can be

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hydrolyzed into water-soluble PEG-polyserine. Copyright 2014 American Chemical

Society.29 ........................................................................................................................... 41

Figure 2.3 Schematic representation of insulin secretion mechanism. Copyright 2015 The

Canadian Society of Clinical Chemists.38 ......................................................................... 43

Figure 2.4 TEM images of (a) AAC1, (b) AAC2, (c) AAC3, (d) AAC4, (e) AAC5, (f)

AAC6, (g) AAC7 in PBS (pH 7.4, 1 day) at 20 mM. ....................................................... 47

Figure 2.5 (a) Cytotoxicity of 6 h-treatment without or with AAC1-3 (0.5, 100, and 500

µM) was measured in 3T3-L1 preadipocytes using lactate dehydrogenase (LDH) activity

assay. Cytotoxicity of (b) 3T3-L1 preadipocytes and (c) human brain endothelial cells

treated with different concentrations of AAC2 or left untreated for up to 72 h. (d)

Cytotoxicity of 3T3-L1 preadipocytes treated with AAC compounds (0.1 μM) or left

untreated for 24 h. (e) Reactive oxygen species concentration was measured in 3T3-L1

preadipocytes stimulated with H2O2 for 4 h (200 μM) and treated with and without AAC

(0.1μM) for 24 h. .............................................................................................................. 49

Figure 2.6 (a) TEM image of the self-assembled structure of AAC2 in PBS. (b) UV-Vis

spectra of AAC2 in TFE and PBS. (c) Co-plot of UV-Vis and CD spectra of AAC2 in PBS.

(d) FT-IR spectrum of AAC2. (e) Thioflavin T binding assay (Excitation: 440 nm and

Emission: 482 nm) of AAC2 in PBS (1 mM, aged for 24 h). (f) Plot of fluorescence

intensity of Nile Red at 656 nm (Ex = 550 nm) versus the concentration (mM) of AAC2 in

PBS. .................................................................................................................................. 51

Figure 2.7 a) Titration of AAC2 (0.1 mM in PBS, pH 7.4) with hINS at different

concentrations. b) TEM image of AAC2-hINS complex. c) Change in frequencies and

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dissipations vs. time for hINS (10µg/mL) and AAC2 nanofiber (0.1µM) on active gold

surface. Insulin were introduced at t=500s. d) Values of thickness of AAC2 nanofiber and

hINS on the active gold surface in real time were calculated to unveil molecular interaction

between AAC2 nanofiber and insulin. .............................................................................. 53

Figure 2.8 (a) Dose-dependent FD-glucose uptake in SVF cells stimulated with AAC2 and

AAC6. (b) FD-glucose uptake in non-treated (Veh) SVF cells or stimulated with AAC2,

or hINS for 80min. (c) Glucose uptake in non-treated (Veh) 3T3-L1 adipocytes or

stimulated with hINS, mLep or AAC2. (d) FD-glucose uptake in human brain endothelial

cells (hBEC) treated with vehicle (Veh; PBS) or hINS, human leptin (hLep), or AAC2 in

the presence and absence of GLUT1 inhibitor. (e) FD-glucose uptake in mouse 3T3-L1

preadipocytes treated with vehicle (Veh;PBS) or hINS, mouse leptin (mLep), or AAC2 in

the presence and absence of GLUT1 inhibitor. ................................................................ 55

Figure 2.9 (a) Dose-dependence FD-glucose uptake stimulated by AAC2 in 3T3-L1

preadipocytes after 100 min of incubation. (b) FD-glucose uptake in non-stimulated (Veh)

or stimulated with AAC2 or hINS in 3T3-L1 cells for 80 min. Prior to stimulation cells

were incubated with Veh, heat-inactivated immunoglobulin (data not shown), or anti-InsR

antibody for 40 min. (c) FD-glucose uptake (% vs. Veh) in presence of AAC2 with and

without PI3K inhibitor or pan-Akt inhibitor in 3T3-L1 preadipocytes. (d) Glucose uptake

in 3T3-L1 preadipocytes mediated by AAC2 with or without inhibitors for various

pathways implicated in glucose uptake............................................................................. 57

Figure 2.10 (a) FD-glucose uptake (% compared to Veh) in presence of AAC2 or

recombinant mouse leptin protein in 3T3-L1 preadipocytes incubated with inactivated

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antibodies or poly clonal anti-LepR antibodies. (b) FD-glucose uptake (% compared to

Veh) in presence of AAC2 or recombinant mouse leptin protein in SVF cells isolated from

subcutaneous fat of Leprdb mouse. .................................................................................... 58

Figure 2.11 (a) Expression of phosphorylated and non-phosphorylated proteins measured

in 3T3-L1 preadipocytes treated with leptin, insulin and AAC2 for 5 or 15minutes using

Western blot. (b) FD-glucose uptake (% compared to Control) in presence in the absence

(Veh) of AAC2 inhuman visceral SVF cells with and without ZIP inhibitor. ................. 59

Figure 2.12 Binding affinity between recombinant mouse leptin receptor protein (LepR)

and leptin (a) or binding affinity between LepR and AAC2 (b); Blue line shows frequency

and orange line shows dissipation. (c) Thickness of LepR-leptin film or LepR-AAC2 film.

........................................................................................................................................... 60

Figure 2.13 (a) GTT in Leprdb mice treated without (Veh) or with AAC2. (b) Food intake

in Leprdb mice treated without (Veh)or withAAC2. (c) Weight gain in Leprdb mice treated

without (Veh) or with AAC2. (d) Insulin levels in plasma of Leprdb mice. (e) GTT in Lepob

mice treated without (Veh) or with AAC2. (f) Food intake in Lepob mice treated without

(Veh) or withAAC2. (g) Weight gain in Lepob mice treated without (Veh) or with AAC2.

(h) Insulin levels in plasma of Lepob mice. ....................................................................... 61

Figure 2.14 (a) Baseline fasting glucose levels prior to treatment in Ins2Akita mice. (b)

Mouse insulin levels measured in same Ins2Akita mice at the end of the study. (c) Food and

(d) water consumption measured in same Ins2Akita mice 7 weeks after treatment.

Respiratory exchange ratio (RER) measured in same Ins2Akita mice during the (e) dark and

(f) light period. (g)GTT in same Ins2Akita mice 3weeks after beginning of treatment. ..... 63

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Figure 2.15 (a) Body weight in Ins2Aktia mice. (b) Percent body fat in Ins2Aktia mice. (c)

Percent lean body mass in Ins2Aktia mice. ......................................................................... 64

Figure 2.16 (a) Brain mass in Ins2Aktia mice. (b) Total movement distance, (c) Amount of

activity in the periphery of the arena and (d) number of rears were conducted using open

field test. (e) Latency time and (f) number of errors measured in the training period. (g)

Hole escape time at day6 (Q3 in same experiment). ........................................................ 65

Figure 3.1 Proposed supramolecular models for a) the gelators Pyr-YL and (Fmoc-YL);

b) the surfactants Fmoc-S and Pyr-S; c) orthogonal PyrYL/Fmoc-S and (Fmoc-YL/Pyr-S);

d) cooperative Pyr-YL/Fmoc-YL and Pyr-S/Fmoc-S; and e) disruptive Pyr-YL/Pyr-S and

(Fmoc-YL/FmocS). Copyright 2014 American Chemical Society.20 ............................... 96

Figure 3.2 a) Structures of gelators 1 (top) and 2 (bottom); b) Hydrolysis of GdL to

gluconic acid. Copyright 2013 Nature Publishing Group, a division of Macmillan

Publishers Limited.22......................................................................................................... 97

Figure 3.3 Proposed mechanism of the twisted ribbons, belts and fibrils formation by the

peptides EFFFFE, and EFFFFK, EFFFFE/KFFFFK mixture, and KFFFFK. Copyright

2015 American Chemical Society.26 ............................................................................... 100

Figure 3.4 Structures of AAC7 and AAC4’.................................................................... 102

Figure 3.5 TEM images of AAC7 in HPLC grade water after a) 1 day and b) 1 week. The

sample were prepared at 5 mM and diluted to 1 mM for microscopic studies. .............. 103

Figure 3.6TEM images of AAC4’ in HPLC grade water after a) 1 day and b) c) 1 week.

The sample were prepared at 5 mM and diluted to 1mM for microscopic studies. ........ 104

xvii

Figure 3.7 Deconvoluted FT-IR spectra of a) AAC7 and b) AAC4’. The samples were

prepared in D2O (5 mM) and set for 1 week. Then the samples were lyophilized for 2 days

to remove solvent and redissolved in D2O (5 mM) for measurement. c) Calculated

percentage of secondary structures of AAC7 and AAC4’. ............................................. 105

Figure 3.8 CD spectra of a) AAC7 and b) AAC4’; UV-Vis spectra of c) AAC7 and d)

AAC4’. AAC7 and AAC4’ were self-assembled in HPLC grade water (5 mM) for a week.

Monomeric samples were prepared by dissolving AAC7 and AAC4’ in TFE (5 mM). The

spectroscopic experiments were performed at 5 mM in a 0.1 mm quartz cuvette. Co-plot of

CD and UV-Vis spectra of e) AAC7 and f) AAC4’. ...................................................... 108

Figure 3.9 TEM images of AAC7 self-assembled in HPLC grade H2O at a)1 mM and b)

0.5 mM; TEM images of AAC4’ self-assembled in HPLC grade H2O for 5 days at c) 1 mM

and d) 0.5 mM. ................................................................................................................ 110

Figure 3.10 CD spectra of a) AAC7 and b) AAC4’ and UV-Vis spectra of c) AAC7 and d)

AAC4’ at 5 mM, 1 mM, 0.5 mM in HPLC grade water and 5 mM in TFE. .................. 112

Figure 3.11 Zeta potentials of AAC4’ and AAC7 at 1 mM in HPLC grade water. ....... 113

Figure 3.12 a) Co-plot of CD and UV-Vis spectra and b) TEM image of AAC7:AAC4’

(1:1) mixture. AAC7 and AAC4’ were pre-assembled in HPLC grade water at 5 mM for 1

week and then combined in 1:1 ratio by volume. The mixture was set at room temperature

for 3 days and diluted to 1 mM for spectroscopic and microscopic studies. .................. 114

Figure 3.13 a) CD spectra and b) UV-vis spectra of pre-assembled AAC7:AAC4’ (2:1) and

(5:1) mixtures. TEM image of c) pre-assembled AAC7:AAC4’ (2:1) mixture and d) pre-

assembled AAC7:AAC4’ (5:1) mixture. AAC7 and AAC4’ were self-assembled in HPLC

xviii

grade water (5 mM) separately for 1 week, then the samples were made by combining

AAC7 and AAC4’ in different ratios by volume. ........................................................... 116

Figure 3.14 Co-plot of theoretical (dash line) and experimental (solid line) CD spectra of

AAC7:AAC4’ at 1:1, 2:1 and 5:1 ratio. Theoretical CD spectra were obtained from simple

ratiomatic combination of data from AAC7 and AAC4’. ............................................... 118

Figure 3.15 Deconvoluted FT-IR spectra of pre-assembled AAC7:AAC4’ mixtures at ratio

of a) 1:1, b) 2:1 and c) 5:1. d) Co-plot of FT-IR spectra of pre-assembled AAC7:AAC4’

mixtures, AAC7 and AAC4’. AAC7 and AAC4’ were prepared in D2O (5mM) and set for

1 week. Then the samples were combined in different ratios, set at room temperature for 3

days and then lyophilized for 2 days to remove solvent. The dried samples were redissolved

in D2O for measurement. e) Calculated percentage of secondary structures in pre-

assembled AAC7:AAC4’ mixtures................................................................................. 120

Figure 3.16 Normalized fluorescence spectra of AAC4’ and pre-assembled AAC7:AAC4’

mixtures in 1:1, 2:1 and 5:1 ratios. All samples were diluted from 5 mM to 1 mM.

Fluorescence spectra were measured using 3 mM quartz cuvette. The samples were excited

at 350 nm......................................................................................................................... 122

Figure 3.17 TEM images of co-assembled AAC7:AAC4’ at ratios of a) 1:1; b) 2:1; c) 5:1.

The samples were prepared at 5 mM and diluted to 1 mM for microscopic studies. ..... 123

Figure 3.18 a) CD spectra and b) UV-Vis spectra of co-assembled AAC7:AAC4 at 1:1, 2:1

and 5:1 ratios. The samples were prepared at 5 mM in HPLC grade water with 10% TFE

and diluted to 1 mM for spectroscopic and microscopic studies. ................................... 124

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Figure 3.19 Deconvoluted FT-IR spectra of co-assembled AAC7:AAC4’ mixtures at ratio

of a) 1:1, b) 2:1 and c) 5:1. AAC7 and AAC4’ were first dissolved in TFE (5 mM),

combined in different ratios and lyophilized. The dried mixtures were dissolved in D2O

with 10% TFE (5mM) and set for 1 week and then lyophilized for 2 days to remove solvent.

The samples were redissolved in D2O for measurement d) Co-plot of FT-IR spectra of co-

assembled AAC7:AAC4’ mixtures, AAC7 and AAC4’................................................. 126

Figure 3.20 Normalized fluorescence spectra of AAC4’ and co-assembly of AAC7:AAC4’

in 1:1, 2:1 and 5:1 ratios. All samples were diluted from 5 mM to 1 mM. Fluorescence

spectra were measured using 3 mM quartz cuvette. The samples were excited at 350 nm.

......................................................................................................................................... 127

Figure 3.21 Proposed AAC7:AAC4’ self-assembly. a) AAC7 and AAC4’ are pre-

assembled in water to yield distinct nanostructures. Pre-assembled AAC7 and AAC4’ form

the complex showed on the right via electrostatic attraction. b) AAC7 and AAC4’ are

combined in monomeric form. The co-assembled nanofibers comprise segments of AAC4’

and AAC7. ...................................................................................................................... 128

xx

List of Abbriviations

A alanine

α alpha

Å Angstrom

R arginine

KATP ATP-sensitive potassium channel

β beta

CNS central nervous system

CD circular dichoism

Con A concanavalin A

J coupling constant in Hz (NMR)

CMC critical micelle concentration

C cysteine

°C degrees Celsius

D dextrorotary

DLS dynamic light scattering

DMF dimethylformamide

GPCR G protein-coupled receptor

GLP glucagon-like peptide

xxi

GdL glucono-δ-lactone

GTT glucose tolerance test

GLUT glucose transporter

E glutamic acid

G glycine

HPLC high performance liquid chromatography

hBEC human brain endothelial cells

hINS human insulin

IR infrared

InsR insulin receptor

I isoleucine

K lysine

L liter (s); levorotatory; leucine

pH -log[H+]

mTOR mammalian target of rapamycin

μ micro

m milli; meter(s); multiplet (NMR)

M moles per liter

NMR nuclear magnetic resonance

1D one dimensional

ppm parts per million

PA peptide amphiphile

xxii

F phenylalanine

PBA phenylboronic acid

π pi

PEG polyethylene glycol

AKT protein kinase B

PKC protein kinase C

RER respiratory exchange ratio

S serine

STAT signal transducer and activator of transcription protein

SVF stromal vascular fraction preadipocytes

ThT thioflavin T

3D three dimensional

TEM transmission electron microscopy

TES triethylsilane

TFA trifluoroacetic acid

TFE trifluoroethanol

t triplet (NMR)

2D two dimensional

T1D type 1 diabetes

T2D type 2 diabetes

Y tyrosine

UV ultraviolet

xxiii

V valine

Vis visible

λ wavelength

1

Chapter 1 Peptide Self-assembly in Aqueous Medium

1.1 Introduction

Molecular self-assembly is a spontaneous and reversible process which disordered

molecular units form organized structures as a result of non-covalent interactions, such as

hydrogen-bonding, hydrophobic interaction, van der Waals forces, π - π interaction and

electrostatic attraction/repulsion. Self-assembly is ubiquitous in nature (Figure 1.1) and it plays a

vital role in life. Many structures in physiological system form through self-assembly process,

such as phospholipid lipid bilayer structure of cell membrane, double helix of DNA and formation

of protein structures. Self-assembly not only plays a significant role in biological system, it also

inspires scientists to design dynamic and functional nanomaterials. In fact, self-assembly has been

extensively studied in recent decades and self-assembled materials have been applied in different

fields including tissue engineering1-4, targeted drug delivery5-7, optoelectronics8-10, etc. The

progress and achievement on the field allow scientists to have profound understanding on

mechanisms of molecular self-assembly11-16 and design molecules that yield predictable

morphology and desired functions.17, 18

2

Figure 1.1 Self-assembled structures in nature.

1.2 Significance of Water

Water is a unique solvent for self-assembly.19 All biological processes take place in water

and nature uses water as a medium to achieve complex, adaptable and robust structures.20 The

unique properties of water are, on certain level, attributed to its ability to form weak hydrogen

bonding which allows biomolecules to reorient in specific configurations and form distinct three

dimensional structures.21 The specific interactions between biological subunits in water has

enlightened researchers to design new supramolecular systems in aqueous condition and aqueous

supramolecular polymers could be beneficial since they have high biocompatibility. Furthermore,

water, as a solvent, is economical, highly accessible and it has minimal ecological impact.19

1.3 Non-Covalent Interactions of Self-assembly in Water

Hydrophobic Effect

The hydrophobic effect is one of the fundamental driving forces of self-assembly in

aqueous solvent. The hydrophobic effect is generally considered to have entropic origin. When

3

hydrophobic molecules are introduced to aqueous environment, water molecules will initially form

static clusters around the hydrophobic group and lose mobility.21, 22 The initial accommodation of

hydrophobic molecules in water is entropically unfavorable. Thus, the hydrophobic molecules will

aggregate, and water molecules will be released to regain faster dynamics and entropy will

increase.23 Furthermore, compensation of enthalpy can also affect hydrophobic effect. If a large

hydrophobic group is introduced to aqueous medium, multiple hydrogen bonds in the solvent will

be broken.24 To compensate the enthalpic cost, hydrophobic molecules aggregate in order to

minimize the interfacial area with water molecules. In this case, both entropy and enthalpy have

impacts on the hydrophobic effect. It is considered by some researchers that the hydrophobic

effect is the major driving force for self-assembly processes and plays a vital role in life. The self-

assembly of phospholipids is an excellent example. Phospholipid molecules consist of hydrophilic

head and hydrophobic tail.25 Driven by hydrophobic effects, the non-polar tails of phospholipids

aggregate together to avoid contact with aqueous environment and eventually bilayer structure is

formed, which is the basis of cell and other organelles formation. Amphiphilic molecules like

phospholipids can form nanoscale vesicles and micelles, which are now widely applied in drug

delivery systems and other biomedical uses.26-28

Hydrogen Bonding

Hydrogen bonding is particularly important for self-assembly of peptides since hydrogen

bonds form between peptide amide bonds. The selective and highly directional nature of hydrogen

bonds can induce peptides assemble into distinctive 1-dimensional (1-D), 2-D and 3-D

4

nanostructures.11 Hydrogen bonding is considered a rather strong intermolecular force and the

strength of hydrogen bonds mostly lie between 4 and 10 kJ mol-1 (5–10 kT) per bond at 298 K. 29

Hydrogen bonds exist between electronegative atoms with free electron lone pairs (e.g., oxygen

and nitrogen) and hydrogen atoms covalently bound to similarly electronegative atoms.30

Hydrogen bonding is the major driving force for DNA and protein assembly. Secondary structures

of proteins like α-helices and β-sheets are formed from special arrangements of hydrogen bonds

and many of these secondary structures play important roles in disease development. For example,

water-assisted hydrogen bonding is believed to a key to protein fibrillation process, which is

considered as a critical element for Alzheimer disease.31

π - π Interaction

π - π interaction is the non-covalent, attractive interaction between two aromatic

molecules.32 The interaction originates from the attraction between the pi orbitals of an aromatic

molecule and the pi orbitals or electropositive atoms of another aromatic molecule. The two most

stable forms of π - π interaction are parallel-displaced and T-shaped conformation (Figure 1.2).33

π - π interaction is commonly seen in biological systems and it play an important role in life, one

example is that it maintains structural stability of proteins due to preferential binding enthalpy.34

Studies also showed that π - π interaction is vital for molecular recognition35 and it is widely used

in drug design.36 In recent years, the impact of π - π interaction on self-assembly process are also

well-studied.37-39

5

Figure 1.2 Two typical π - π interaction: parallel-displaced and T-shaped.

Van der Waals Forces

Van der Waals forces comprise Keesom forces, Debye forces, and London (dispersion)

forces.40 (Figure 1.3) They originate from dipole or induced dipole interactions. Van der Waals

forces are generally weak (~5kJ mol-1)29 and they have very little influence on self-assembly in

most cases, though van der Waal forces can still affect the self-assembly of molecules with

aliphatic chains, especially within monolayered and multilayered films.41

Figure 1.3 Three components of van der Waals forces. Copyright 2017 Elsevier Inc.40

Electrostatic Forces

Electrostatic interaction between two charged moieties is also an important factor for self-

assembly. It can be either repulsive as the molecular subunits have the same charge, or attractive

as the molecular subunits have opposite charges. Electrostatic attraction is much stronger than

6

other intermolecular forces in organic solvent, with strength of approximately 500 kJ mol-1 and

range up to 50 nm.29, 42 However, electrostatic attraction is greatly weakened in water due to the

high polarity. Therefore, electrostatic interactions are considered to affect self-assembly in

combination with other molecular interactions.43

1.4 Assemblies of Peptides and Peptide Derivatives in Water

Nowadays, fabricating natural building blocks like peptides, phospholipids,

oligonucleotides and oligosaccharides has been a novel path to develop new materials.44 Among

materials employed for self-assembly studies, peptides have drawn great attention due to their

advantages. Peptides have relatively simple structures and they are stable both physically and

chemically.45 There are 20 L-amino acids in nature and the side chains of amino acids are versatile

in size, hydrophobicity and charge, which diversifies synthetic sequences and self-assembled

morphologies. Furthermore, it is feasible to synthesize peptides in large scale, which guarantees

accessibility of the materials. Also, peptides are highly biocompatible and biodegradable45 and

such features enable applications in medical treatments and pharmaceutical industries.

Since early 1990s, peptidic supramolecular materials have been studied in depth, and a

great number of self-assembled architectures formed from peptides has been developed, such as

spheres, fibers, tubes, tapes, extended sheets, etc.45-47 The design of self-assembled peptides can

come from either adapting biological structures like elastins,48 collagens,49 α-helices and β-

sheets,50 or synthesizing novel structures like cyclic peptides or peptide derivatives functionalized

with aliphatic groups and/or aromatic groups.

7

Cyclic Peptides

The self-assembly of cyclic peptides are formed by stacking of peptide subunits (Figure

1.4). The flat, ring-shaped peptides can assemble to hydrogen-bonded hollow tubular structure

with side chains perpendicularly pointing outward.51, 52 Pioneer work of cyclic peptide assemblies

was carried out by Ghadiri and his co-workers in Scripps Research Institute.51-55 In their earliest

work,51 they synthesized a novel cyclic octapeptide cyclo[(D-Ala-Glu-D-Ala-Gln)2. They

hypothesized that the alternation of L- and D-amino acids enabled cyclic peptide to adopt a low-

energy, flat conformation. The peptide subunits were able to assemble into nanotubes with internal

diameters between 7-8 Å under acidic conditions. FT-IR and electron diffraction studies revealed

that the peptides formed anti-parallel β-sheet structures. Based on preliminary studies, Ghadiri and

his co-workers demonstrated that the internal diameter of the peptide nanotubes can be controlled

by adjusting the size of the cyclic peptide.52 By increasing the number of residue from 8 to 12,

they obtained nanotubes with uniform internal diameters of ~13 Å. The research team also

proposed that the formation of the nanotubes was attributed to the cooperative nature of the

assembly process which hydrogen-bonding motif and hydrophobic interactions were

simultaneously involved.54

8

Figure 1.4 Tubular structures formed from self-assembly of cyclic peptide. Copyright 1996

American Chemical Society.54

Applications of the cyclic peptides have also been studied by the same group as they

designed a cyclic octapeptide cyclo[-(Trp-o-Leu)3Gln-D-Leu-].56 It was hypothesized that

decoration of hydrophobic residues on the peptide allowed formation of transmembrane channels

to form in lipid bilayer of cell membrane, which could be a potential vehicle for drug delivery and

gene therapy. They also discovered that formation of hollow tubular structures from cyclic

peptides in bacterial cell membrane could increase membrane permeability, collapse

transmembrane ion potentials, and cause rapid cell death, which could potentially be a new class

of antibacterial agent.57

9

Figure 1.5 Hierarchical assembly to hollow macrotubes. Copyright 2004 WILEY‐VCH Verlag

GmbH & Co. KGaA, Weinheim.58

Zhao and Dory reported a cyclic peptide (Figure 1.5) that formed hexagonal hollow tubes

with diameters in the range of micrometers and length reaching several millimeters.58 Molecular

dynamic studies suggested that individual cyclic peptides stacked up and formed nanotubes, which

further organized into larger hollow tubes which were later observed by SEM. In recent years,

Perrier and Jolliffe synthesized a series of cyclic octapeptides with alternating L and D chirality.

The peptides were conjugated with hydroxyethyl acrylate, acrylic acid and poly(2-ethyl-2-

oxazoline).59, 60 The peptides all self-assembled into nanotubes which were either pH-responsive

or thermo-responsive and the assembly was investigated in detail using different techniques, such

10

as dynamic light scattering (DLS), TEM, and small angle neutron scattering. The authors also

introduced a new series of cyclic peptide conjugates with hydrophobic or hydrophilic polymer

chains.61 By varying the molecular weight of the side chains, they discovered the correlation

between the lipophilicity of the peptide and the proton transfer activity of the transmembrane

channel formed by the peptide conjugates.

Linear Peptides

Besides self-assemblies from cyclic peptide, a large number of linear peptides were

synthesized and shown to be able to self-assemble into various nanostructures. In 2003, Gazit and

his co-worker reported the self-assembly of a short dipeptide NH2-Phe-Phe-COOH (FF) into

nanotubes (Figure 1.6), which could reduce ionic silver and generated long, discrete silver

nanowires.62 In following years, self-assembly of FF was investigated in detail by the same

research group.63-65 Several other groups have explored the properties of FF as well. Park and co-

workers reported that FF can self-assemble into nanotubes and nanowires with high stability

against thermal, chemical and proteolytic attacks.66 Görbitz demonstrated that the X-ray powder

diffraction pattern of FF nanotubes is was identical to the single crystal structure.67 As a minimalist

building block, FF motif has been popular in the field of nanomedicine since binding drug

molecules and/or imaging agents that FF dipeptide can help improve the delivery of some

hydrophobic or unstable molecules to the cells.68

11

Figure 1.6 Dipeptide NH2-Phe-Phe-COOH and its self-assembled nanotubes. Copyright 2003,

American Association for the Advancement of Science.62

Aside from the FF dipeptide motif discovered by Gazit’s group, Ventura and co-workers

investigated the properties of dipeptides NH2-Ile-Phe-COOH (IF) and NH2-Val-Phe-COOH (VF).

The research team found that dipeptide IF could self-assemble into fibrillar networks and become

a transparent, thermoreversible hydrogel. While dipeptide VF was not able to form any

supramolecular structures, even though it only differed from IF by one methyl group. The research

team proposed that slight changes of hydrophobicity could affect the self-assembly process and

assembly of IF could be similar to Aβ42 peptide.69

Hartley’s group discovered the importance of chirality for self-assembly. The group found

that changing the chirality of the first N-terminal amino acid from VFF and FFV, which were not

able to self-assemble at physiological pH, to DVFF and DFFV can result in distinct self-assemblies

12

(Figure 1.7).70 The group also investigated DLFF and its epimer LFF. Similar behaviors to

tripeptides reported in the previous publication were observed. Only DLFF can self-assemble into

long fibers and form hydrogels, while LFF generated heterogenous self-assemblies and failed to

form self-supporting gels.71 In a later publication, the authors demonstrated that subtle changes in

chirality on each amino acid along the tripeptide FFV can affect the conformation and behavior of

self-assembly. Particularly, the two enantiomers DFFV and FDFDV showed high viability and

proliferation of mammalian cells in vitro, whereas they were not cytotoxic in solution.72

Figure 1.7 Tripeptide sequences; hydrogels and nanostructures formed by DVFF and DFFV.

Copyright 2012, The Royal Society of Chemistry.70

Verma and co-workers reported the self-assembly of tetrapeptide PWWP, which was

derived from the antimicrobial peptide indolicidin sequence. The peptide formed vesicles and

addition of KCl could disrupt the structures.73 Miller and co-workers introduced an ionic-

complementary tetrapeptide FEFK. The research group investigated the self-assembly of FEFK

resulting from reverse hydrolysis triggered by protease thermolysin. The main product of this

system was an octapeptide, which was thermodynamically favored and its concentration depended

on the initial concentration of FEFK.74

13

Hamley and co-workers investigated the self-assembly of pentapeptide KLVFF, which was

a fragment derived from amyloid peptide. Experimental results revealed that self-assembly of

KLVFF was influenced by aromatic interactions between phenylalanine units on the peptide and

KLVFF formed -sheet amyloid fibrils in diluted aqueous solution. In phosphate-buffered saline

solution, KLVFF gelated and the gelation was believed to result from electrostatic charge

screening on the peptide, which allowed -sheet amyloid fibrils to aggregate in to a gel network.75

Based on the KLVFF motif, Hamley and co-workers introduced a new peptide AAKLVFF by

extending the pentapeptide with two alanines at the N-terminus. Self-assembly into twisted

nanoribbons in water was observed. Further studies showed that AAKLVFF did not form well-

defined -sheet structure in diluted aqueous solution but in dried film. It was also observed that

well-defined fibrils can be generated from assembling small subunits of AAKLVFF in films dried

from diluted solution. Such phenomenon may allow AAKLVFF to be a good candidate to study

amyloid fibrillization.76 The research group also synthesized octapeptide YYKLVFFC using the

KLVFF motif. The octapeptide was design with multiple residues to investigate how aromatic

interactions and electrostatic interactions affect the self-assembly of the peptide. Also, addition of

two tyrosines introduced pH-induced phenol-phenolate transition and pH effect on self-assembly

of YYKLVFFC was observed that YYKLVFFC self-assembled into long nanofibers at pH 4.7 and

transformed into twisted short nanofibrils at pH 11.77

Saiani and co-workers investigated the self-assembly of four ionic-complementary

octapeptides: AEAEAKAK, AEAKAEAK, FEFEFKFK and FEFKFEFK. Alanine-based peptides

formed α-helices and phenylalanine-based peptides adopted -sheet conformation. Self-assembly

was not observed for AEAKAEAK. AEAEAKAK was found to form fibers with diameter of ~6

14

nm but gelation for AEAEAKAK was not observed even at concentration up to 100 mg mL-1.

FEFEFKFK and FEFKFEFK were found to self-assembled and form hydrogels at concentration

of 8 mg mL-1. Morphologies of both peptides were similar and both hydrogels contained a

homogeneous dense network of semi-flexible fibers.50 Saiani et al. later reported self-assembly

studies of octapeptide FEFEFKFK in detail. The gelation process of FEFEFKFK was investigated

as a function of media pH. At low (<6) and high (>8) pHs, FEFEFKFK formed fibers with distinct

morphologies (Figure 1.8) and hydrogels had different mechanical properties. When pH was in the

range of 6-8, only large bundles of fibers were observed.78

15

Figure 1.8 Self-assemblies of FEFEFKFK at pH 2.8, 4 and 10. Copyright 2013, The Royal

Society of Chemistry.78

Hartgerink and co-workers designed a series of multidomain peptides which had ABA

motifs. Domain B was composed of alternating hydrophilic (glutamine) and hydrophobic (leucine)

amino acids, which enabled peptides to form extended -sheets. Domain A contained a segment

of positively charged lysines at pH 7 and electrostatic repulsions of domain A can work against

self-assembly driven by domain B. The force balances between A and B were studied and it is

noteworthy that the length of nanofibers formed from peptide K2(QL)6K2 can be controlled by

16

changing electrostatic strength of solvent media.79 Based on the same motif, the authors introduced

three other multidomain peptides K2(SL)6K2, E2(SL)6E2 and K2(QL)6K2, which were able to form

hydrogels. The authors also demonstrated that the nanofibers form by peptides with lysine domains

can cross-link using lysyl oxidase or plasma amine oxidase. The mechanical strength of the

hydrogel increased after cross-linking and it is considered that this method may have great

potential in biomaterial applications.80

Aliphatic Peptide Derivatives

Although self-assembly of peptides can generate various nanomaterials, modifying

peptides with different functional groups can enrich the variety of nanomaterials and lead to new

applications. One of the most successful strategies is attaching hydrophobic functional groups on

peptides and making them peptide amphiphiles. Aliphatic peptides are one of the representatives

that are essentially composed of hydrophobic alkyl or lipid chains and hydrophilic peptide

segments. Early studies of aliphatic peptide amphiphiles were focused on their bioactivities. Tirrell

and co-workers introduced a dialkyl peptide amphiphile and its cell membrane mimicry behaviors

were studied.81 In later publications, the authors also synthesized peptide amphiphiles with

collagen-model head groups and dialkyl chain tails and investigations of self-assembly showed

that the peptide amphiphile adopted triple-helical structures.82, 83

Stupp’s lab have successfully designed a series of aliphatic peptide amphiphiles. In 2001,

Stupp and co-workers reported the self-assembly of an aliphatic peptide amphiphile. The peptide

amphiphile assembled into long nanofibers by pH induction (Figure 1.9). The nanofibers were able

to form hydrogels, which could mimic extracellular matrix. The nanofibers could also reversibly

17

cross-link by formation/reduction of intermolecular disulfide bonds. Additionally, hydroxyapatite

mineralized along the long axis of the cross-linked nanofibers and such alignment was also

observed in bone structure.84 This pioneering discovery showed the potential of aliphatic peptide

amphiphiles in biomedical applications and it has drawn researchers’ attention to the field of

aliphatic peptide study.

18

Figure 1.9 A. Chemical structure of the peptide amphiphile. B. Molecular model of the PA. C.

self-assembly of PA molecules into a cylindrical micelle. Copyright 2001, The American

Association for the Advancement of Science.84

Since the ground-breaking publication in 2001, Stupp’s group has consecutively reported

studies of multiple aliphatic peptide amphiphiles. The design of the peptide amphiphiles often

consist of a long aliphatic tail, followed by a peptide sequence with high tendency to form -sheet

and charged residues to enhance solubility in water. Occasionally, the hydrophilic end of the

amphiphile molecule is coupled with a spacer to allow more flexibility to combine with bioactive

molecules.12 The research group have extensively studied the factors that affect self-assembly of

19

aliphatic amphiphiles. Twelve peptide amphiphile derivatives were synthesized to form

nanofibers. The researchers discovered that peptide sequence and aliphatic tail length can influence

morphology and surface chemistry of self-assembly.85 In following studies, the research group

demonstrated that modification of aliphatic tail and peptide sequence affected -sheet character of

nanofiber assembly and bioactivity of nanofibers could be controlled by modifying peptide

amphiphiles.86 Formation of flat nanobelts had also been reported. Peptide amphiphile C16O-

VEVE formed nanobelts with monodispersed width of 150 nm. Interestingly, increasing the pH

resulted in transformation from flat, smooth nanobelts to grooved nanobelts, which was caused by

change in electrostatic interactions between the peptide segments. Also, in diluted solution, the

nanobelt was unraveled to twisted nanofibers.87

Stupp’s group have also broadly studied applications of aliphatic peptide amphiphiles in

the biomedical field. The authors reported a new peptide amphiphile that was able to rapidly induce

differentiate progenitor cells into neurons without astrocytes development, by encapsulation with

three-dimensional nanofiber network formed by self-assembly of peptide amphiphiles with cell

suspension in media.88 The research group also demonstrated that nanofibers generated from

peptide amphiphile (KLAKLAK)(2) can induce breast cancer cell death by membrane disruption

and the process was divergent from caspase-independent and Bax/Bak-independent mechanisms.

The self-assembled (KLAKLAK)(2) showed higher selectivity on inducing cell death in

transformed breast epithelial cells than in untransformed cells, which indicated that peptide

amphiphiles with rational design could form nanofibers that effectively target cancer cells.89 In a

more recent publication, the authors introduced a peptide amphiphile with additional polyethylene

glycol (PEG) chain. The peptide amphiphile self-assembled into nanofibers (Figure 1.10) and

20

pegylation of peptide amphiphile significantly increased the stability of nanofibers against protease

trypsin activity. Using an orthotopic mouse xenograft model of breast cancer, administration of

pegylated peptide amphiphile nanofiber showed promising reduction of tumor cell proliferation

and overall tumor growth, indicating that the pegylated peptide amphiphile had high potential in

cancer treatment.90

21

Figure 1.10 A. Chemical structures of peptide amphiphile KLAK PA and pegylated amphiphile

PEG PA. Cryo-TEM of KLAK PA alone (B). KLAK with PEG (D) shows a significant

difference in average length. Conventional TEM images show fiber formation for both KLAK

alone (C) and KLAK PA with PEG PA (E). Copyright 2012 American Chemical Society.90

Hamley’s group have reported studies on aliphatic peptide amphiphiles as well. In 2010,

the group demonstrated the self-assembly of a commercially available peptide amphiphile C16-

KTTKS, which is also known as Matrixyl. The peptide amphiphile can stimulate collagen

production on skin and hence it is widely used in anti-aging skincare products.91 C16-KTTKS

22

formed macroscale fibrillar structures, which were based on nanotapes with widths ranging from

10 to 100 nm. SAXS results indicated that the peptide amphiphiles formed bilayer structures.

Understanding the self-assembly of this peptide amphiphile could help in developing next

generation collagen-stimulating peptide amphiphiles.92 In later publication, Hamley and co-

workers investigated the self-assembly behaviors of C16-KTTKS (TFA salt) in water at different

temperature. Proton NMR and SAXS results showed that C16-KTTKS reversibly transformed from

nanotapes to micelles as temperature increased and such behaviors were not found in preliminary

studies for aliphatic peptide amphiphiles.93 The same research group also reported that the self-

assembly of C16-KTTKS was controlled by pH. At pH 4, C16-KTTKS formed twisted nanofibers

and at pH 3 flat ribbons were observed. As pH dropped to 2, only micelles were seen. Surprisingly,

the self-assembly transformed into ribbons again when pH was increased to 7. The pH-responsive

behaviors of C16-KTTKS may also shed some light on biomedical application of this peptide

amphiphile.94

Van Hest and co-workers design a fiber-forming peptide amphiphile with peptide sequence

GANPNAAG and hydrophobic tail with diacetylene moiety attaching on N-terminus. The group

discovered that if nonaligned nanofibers were irradiated with polarized light, polymerization only

happened to the fibers that were parallel to the polarized direction (Figure 1.11). The fibers were

aligned magnetically and selectively polymerized using polarization holography.95 The same

group synthesized three peptide amphiphiles with hydrophobic tails containing diacetylene in

different positions. Experimental results indicated that the position of diacetylene on the aliphatic

chain affected the stability of self-assembly and chromatic properties.96

23

Figure 1.11 (a) The peptide amphiphile used for the polarization-sensitive polymerization

experiments. (b) The polymerization that occurs upon illumination of a diacetylene. (c)

Dependent on the polarization direction of the light (the arrows), one or the other orientation of

the fibers will polymerize. The darkness of the lines depicts their degree of polymerization. A

black line is fully polymerized, and light gray is nonpolymerized. Copyright 2009 American

Chemical Society.95

Aromatic Peptide Derivatives

Besides utilization of aliphatic groups in peptide derivative design, aromatic groups can

also be employed since π - π interaction is a major driving force for self-assembly. In general,

aromatic peptide derivatives consist of a short peptide sequence and an aromatic moiety which is

often capped on the N-terminus (Figure 1.12). Fluorene, naphthalene, pyrene, azobenzene and

24

phenyl derivatives are some of the most common aromatic moieties used in aromatic peptide

derivative design. A linker segment is sometimes added between the aromatic group and the N-

terminus of the peptide. The C-terminus of the peptide derivative can also be functionalized.17

Much work has been carried out on aromatic peptide derivatives and it is no doubt that aromatic

peptide derivatives are now a significant subset of peptide self-assembly.

Figure 1.12 Example of aromatic peptide derivatives. Copyright 2014 The Royal Society of

Chemistry.17

Pioneering work was reported by Vegners and co-workers in 1995. Dipeptide derivative

Fmoc-LD was synthesized and thermoresponsive behavior of Fmoc-LD hydrogel was observed.

The hydrogel was used as a carrier to incorporate with non-antigenic antiviral drugs and injected

into rabbits, which successfully induced antibody production without additional adjuvant.97 In

2003, Xu and co-workers synthesized a series of Fmoc-dipeptides 1-7 (Scheme 1). Gelation was

observed in all peptides and hydrogels 1, 3 and 4 converted to suspensions in respond to ligand-

receptor interaction.98 Based on ligand-receptor interactions, Xu’s group later reported a novel

strategy to enhance mechanical strength of hydrogels self-assembled from small molecules.

Vancomycin was chosen as the receptor and added to a hydrogel formed from ligand peptide

pyrene-DADA. The storage modulus of the hydrogel of pyrene-DADA increased by 106-fold after

25

addition of the receptor. Spectroscopic and microscopic experiments revealed that molecular

recognition between vancomycin and pyrene-DADA and dimerization of vancomycin led to the

conspicuous increase in elacity.99 The same research group also demonstrated utilization of

kinase/phosphatase switch to regulate self-assembly of nanostructures and formation of hydrogels.

Naphthalene-based hydrogelator Nap−FFGEY was synthesized. Phosphorylation of tyrosine

residue on the peptide derivative by kinase resulted in a gel−sol phase transition and

dephosphorylation by phosphatase regenerated the hydrogel. Subcutaneous injections to mice

indicated that the phase transition also occurs in vivo.100

Scheme 1.1 Structures of Fmoc-dipeptide 1-7. Copyright 2003 American Chemical Society.98

Ulijn’s group have also developed a series of aromatic peptide derivatives since mid-2000s.

The group investigated the self-assembly of dipeptide derivative Fmoc-FF. A model of anti-

parallel -sheets connected by π-π interactions of Fmoc groups and phenyl groups was proposed.

Spectroscopic experiment results were consistent with the author’s explanation.101 The research

group reported the study of mechanosensitivity of hydrogel formed from Fmoc-FF in later

publication. Particularly, the group demonstrated that using different homogenization techniques

during gelation process can significantly influence the mechanical properties and self-assembly of

26

the hydrogel.102 The research group also synthesized three new peptide derivatives Fmoc-FG,

Fmoc-GG and Fmoc-GF, and the self-assembly of these peptides were investigated and compared

with Fmoc-FF, which was well-studied in preliminary publications. It was observed that all three

Fmoc-dipeptides were able to self-assemble into nanostructures, which indicated that the major

driving force of self-assembly was π-π interactions between Fmoc groups combining with

hydrogen bonding on the peptide segments. However, the morphologies of the nanostructures were

different (Figure 1.13). This observation showed that replacement of phenylalanine by glycine

affected the flexibility103 of the dipeptide and further changed the conformation of the self-

assembly.104 Ulijn’s group have reported studies on enzyme-assisted self-assembly of aromatic

peptide derivatives as well.105-108 Enzyme-assisted self-assembly shows a novel way to control

self-assembly at a nanoscale level. The reversibility and biocompatibility of the process also

provides a new platform for biomedical and electronic material research.

Figure 1.13 TEM images and actual samples of Fmoc-FG, Fmoc-GG and Fmoc-GF. Copyright

2011 American Chemical Society.104

27

The Adams group has reported self-assembly of various aromatic peptide derivatives as

well. In 2010, the research group synthesized peptide derivative bromonaphthalene-AV and its

self-assembly process was pH-responsive. Hydrolysis of glucono-δ-lactone (GdL) to gluconic acid

was employed to adjust the pH of the peptide solution. Furthermore, this method allowed kinetic

control of the self-assembly and the process could be observed. Microscopic and spectroscopic

experiments revealed that self-assembly process began as the peptide derivative was protonated

(Figure 1.14). Protonation of the carboxylate on the C-terminus of the peptide segment reduced

electrostatic repulsions and then led to self-assembly.109 The research group also investigated how

structural modifications could influence self-assembly and gelation of naphthalene-dipeptides by

varying both the substitution on naphthalene and amino acids on the peptide segment.110 In

addition, the research group also demonstrated the studies of salt-induced hydrogelation with

naphthalene-dipeptide derivatives and they discovered that addition of divalent cation such as Ca2+

at high pH resulted in self-assembly of nanofibers and gelation.111, 112

28

Figure 1.14 TEM of evolution of structures with time for dipeptide in the presence of GdL (14.42

mg/mL): (a) immediately after GdL addition; (b) 40 min, (c) 80 min, (d) 120 min, (e) 160 min,

(f) 200 min, (g) 240 min, (h) 280 min, and (i) 400 min after GdL addition. In all cases, the scale

bar represents 200 nm. Copyright 2009 American Chemical Society.109

29

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36

Chapter 2 Self-assembled Anti-diabetic Amino Acid Compound

(Adapted from “Amino acid-based compound activates atypical PKC and leptin receptor

pathways to improve glycemia and anxiety like behavior in diabetic mice.”

Biomaterials, 239, 119839. https://doi.org/10.1016/j.biomaterials.2020.119839. Cell and

animal studies were performed by Dr. Ouliana Ziouzenkova and Dr. Aejin Lee)

2.1 Introduction

Glucose is a major energy substrate in biological systems and regulation of glucose

homeostasis is critical for life. Insulin is one of the most well-known hormones that

regulates glucose metabolism. In skeletal muscle, liver and adipose tissues, insulin converts

glucose either into glycogen via glycogenesis or lipids via lipogenesis.1 Moreover, insulin

can regulate the major glucose transporter (GLUT4) in peripheral tissues, which supplies

70% of post prandial glucose to muscle tissues and 10% to adipose tissues.2 Impairment

in insulin signaling pathways such as deficient insulin production, misfolding of insulin

and insulin resistance can result in diabetes mellitus.2, 3

In type 1 diabetic (T1D) individuals, insulin has been used as the primary treatment

to maintain glucose homeostasis for a century.4 Insulin also acts as an anabolic hormone

and it supports growth in young individuals and other anabolic processes in all age groups.2,

4 Alternatively to insulin, leptin is used in diabetic treatment as well. Unlike insulin, leptin

is a catabolic hormone and regulates glucose homeostasis in peripheral tissues via

https://doi.org/10.1016/j.biomaterials.2020.119839

37

activating GLUT4 catabolically.5, 6 In T1D individuals, leptin production is often

diminished and treatment with leptin can control glucose homeostasis via peripheral GLU4

activation, compensating for insulin deficiency in T1D individuals.7-9 In addition, leptin

treatment is also effective in leptin-deficient Lepob mice with insulin resistance and

lipodystrophic mice and patients.10, 11 Whilst, in type 2 diabetes (T2D), commonly

accompanied by obesity, leptin resistance is often developed and it limits application of

leptin treatment under this situation.

Apart from peripheral tissues, neural tissues also utilize glucose as primary energy

substrate, which consume up to 20% of daily glucose used in biological systems.12

Regulation of glucose homeostasis in neural tissues is different from that in peripheral

tissues: insulin-insensitive glucose transporters GLUT1 and GLUT3 are highly expressed

in brain tissues, whereas insulin-regulated GLUT4 is abundant in peripheral tissues.13-15

Since GLUT1 is the major glucose transporter in neural tissues, deficiency of GLUT1 can

lead to irreversible neural tissue damage.16, 17 In diabetic individuals, GLUT1 is often

deactivated by decreased leptin production,7 impaired GLUT1 amino acid metabolism18

and/or irregular phosphorylation of protein kinase C (PKC), which is related to GLUT1

translocation in cells.19 Because regulation of glucose homeostasis does not completely

depend on insulin in neural tissues, interruption of insulin signaling pathway in neural

tissues does not impair their functions.20 Moreover, insulin treatment for diabetic patients

results in reciprocal glucose uptake in peripheral tissues and could lead to hypoglycemic

episodes and energy deprivation states in neurons.4, 21

38

In the past few decades, different therapeutics and materials have been developed

for diabetic treatment, most of which act on the canonic insulin signaling pathway. In

1970s, synthesis of human insulin using recombinant DNA technology was developed and

later commercialized in 1980s.4 Since then, a series of insulin analogs were synthesized

and have been used commercially.4 There are two major types of insulin analogs: fast-

acting and basal. Fast-acting insulin analogs can act within 15 minutes after meals to lower

blood sugar level.22 On the contrary, basal insulin analogs are long-acting and peakless in

physiological systems.23

Insulin treatment is mostly administrated by periodic manual injection or electronic

insulin pump. Whereas difficulty in controlling insulin doses during injection and

biofouling in insulin pumps are two of the major shortcomings in traditional insulin

treatment.24 To overcome these problems, glucose responsive nanomedicines were

developed. The design of glucose-responsive nanomedicines are based on the function of

-cells in pancreas and it can release insulin in response to hyperglycemic condition in

blood.24 To achieve the glucose-sensing system, insulin nanocarriers consist of various

molecules25 were engineered with different glucose-responsive triggers.26 Three types of

glucose-responsive triggers are most commonly used: glucose oxidase, glucose-binding

proteins and glucose-binding small molecules.27 To release insulin, the nanocarriers are

designed to disassemble by either swelling or degrading (Figure 2.1).27

39

Figure 2.1 Two different insulin-releasing nanoparticles. Copyright 2014, Nature

Publishing Group, a division of Macmillan Publishers Limited.27

Glucose oxidase is capable of oxidizing glucose into gluconic acid in physiological

environment. pH-responsive polymers are used with glucose oxidase to build glucose-

sensing platforms for insulin release. For example, Zhen’s group designed a nanoparticle

loaded with insulin, glucose oxide and catalase (Figure 2.2).28 Addition of catalase can

convert H2O2, a byproduct from glucose oxidation, to O2 and further promote glucose

oxidation. The nanovesicle was bilayered and comprised amphipilic polymer PEG–

poly(Ser-Ketal), which contained an acid-sensitive ketal end. The polymer bilayer shell

was stable under physiological pH and prevented loss of encapsulated insulin at low blood

sugar level. As glucose levels increased in the system, glucose molecules entered the

nanovesicle by passive diffusion and glucose oxidase catalyzed the oxidation from glucose

to gluconic acid. Increased concentration of gluconic acid triggered the hydrolysis of the

40

ketal group on PEG–poly(Ser-Ketal) and converted it into hydrophilic PEG-polyserine.

The nanovesicle disassembled and eventually released insulin into the system.28 Zhen and

co-workers also developed a novel glucose-responsive insulin delivery device using a

painless microneedle-array patch, which contained nanovesicles loaded with insulin and

glucose oxidase.29 The nanovesicle consisted of hypoxia-sensitive hyaluronic acid

conjugated with 2-nitroimidazole. As glucose got oxidized under hyperglycemic

conditions, the local microenvironment became hypoxic and the 2-nitroimidazole on the

polymer was reduced to a more hydrophilic 2-aminoimidazole, causing the nanovesicle to

dissociate and releasing insulin. The patch showed high efficacy on glucose homeostasis

regulation in chemically induced T1D mice and provided faster response to

hyperglycemia.29

41

Figure 2.2 A) Schematic of the enzyme-based glucose-responsive nanovesicle. B) The

chemical structure of the pH-sensitive polymer PEG-poly(Ser-Ketal), which can be

hydrolyzed into water-soluble PEG-polyserine. Copyright 2014 American Chemical

Society.29

Glucose-binding protein is commonly used as a glucose-responsive trigger.

Concanavalin A (Con A) is a lectin protein extracted from plants. Con A protein can bind

with glucose-specific carbohydrates and it can act as crosslinker between polymers bearing

glucose moieties.30 Under hyperglycemic conditions, Con A can bind with free glucose

molecules and the nanostructure formed by the polymers can swell or disassemble to

release insulin.30 In 2001, Park and co-workers introduced a glucose-sensitive hydrogel

that comprised insulin, glucose-containing polymers and PEGylated Con A. As glucose

concentration increased, the insulin release rate was enhanced.31 Anzai and co-workers

42

have design a series of glucose-sensitive layer-by-layer films using various polymers and

Con A to achieve controlled insulin release in physiological environment.32-35 For example,

glucose-sensitive microcapsules were prepared by layer-by-layer deposition of Con A and

glycogen on calcium carbonate particles loaded with fluorescein-labeled insulin.35 Insulin

was released slowly in the absence of sugar and the releasing rate was accelerated as sugar

concentration increased, which was caused by added sugars replacing glycogen in the

binding site of Con A and consequently enhancing permeability of the capsule layers.35

Small molecules like phenylboronic acid (PBA) represent a chemical approach to

glucose-responsive insulin delivery systems.27 PBA is designed to mimic glucose-binding

proteins, which can bind with glucose-containing polymers and form glucose-responsive

nanostructures. Matsumoto and co-workers introduced a hydrogel that consisted of PBA-

containing polymers. Under hyperglycemic condition, the gel was able to release insulin.36

As glucose reacted with PBA, the gel underwent dehydration and formed a skin layer on

the surface of gel to prevent further release of insulin, which prevented hypoglycemia from

over-release of insulin.36 In later publication, Matsumoto and co-workers developed a PBA

derivative to improve binding specificity to glucose under physiological pH.37

Apart from the insulin delivery nanomedicines mentioned above, medications

called insulin secretagogues for improving insulin secretion are also widely used

specifically on T2D patients. Insulin secretion is initiated by increase of glucose in the

pancreatic beta cell, followed by glycolysis and production of ATP to inhibit the ATP-

sensitive potassium channel (KATP). As KATP shut down, potassium ions build up in

cytoplasm and cell membrane will undergo depolarization. The process will open the

43

voltage-gated calcium channel and lead to the influx of calcium ions, and further stimulate

the release of insulin into the blood (Figure 2.3)38, 39. In diabetic individuals, glucose uptake

of cell is impaired and ATP generation is insufficient in cytoplasm to inhibit KATP and

further trigger insulin secretion. To address this problem, KATP inhibitors are introduced.

Sulfonylurea drugs are one of the most used KATP inhibitors for diabetic management and

generations of sulfonylurea treatment have been developed over decades.40 Glucagon-like

peptide 1 (GLP1) and its synthetic analogs are also well-studied for diabetic treatment.41,

42 GLP1 is a blood glucose-lowering hormone that binds to G protein-coupled receptors

(GPCRs) located on pancreatic β-cells and causes stimulation of insulin gene transcription,

insulin biosynthesis, and insulin secretion.43

Figure 2.3 Schematic representation of insulin secretion mechanism. Copyright 2015 The

Canadian Society of Clinical Chemists.38

44

The diabetic treatments mentioned above are all targeted on the canonic insulin

signaling pathway, which regulates insulin sensitive GLUT4 in peripheral tissues.

However, glucose homeostasis regulated by GLUT1 in peripheral and neural tissues in

diabetic individuals is neglected in this case. As a matter of fact, many treatments that

optimize systemic glucose control are not able to prevent neurodegeneration that

contributes to the development of retinopathies, neuropathies and central nervous system

(CNS) damage in diabetic patients44, 45 and cognitive impairments occur in all age groups.46

Therefore, searching for compounds that can regulate glucose homeostasis via alternative

pathways to work in combination with insulin treatment is significant for diabetic

management. It was reported that some natural di-and polypeptides could have glycemic

properties,47-49 even though proteolytic degradation could limit the efficacy of the peptides.

Likewise, plant extracts like coumarin derivatives demonstrate antidiabetic activity,

although high dosage is required.50 Despite preliminary discoveries, the antidiabetic

properties of compounds consist of both peptides and coumarins are still unknown.

Herein, we demonstrate the syntheses of a series of peptide derivatives that can

self-assemble into various nanostructures. We also investigate the antidiabetic efficacy of

the prototype peptide, which rescues mice models associated with T1D and T2D and

attenuates cognitive deficits.

2.2 Results and Discussion

It was reported that lysine and coumarin derivatives can induce glucose response,51,

52 hence we utilized 7-(diethylamino)coumarin-3-carboxylic acid (DAC) to incorporate

45

with Fmoc-dilysine peptide as the prototype. In addition, to understand the role of charged

amino acid side chain and aromatic moiety play in antidiabetic efficacy, we synthesized

and tested a series of Fmoc-peptide derivatives (Scheme 2.1) termed amino acid compound

(AAC). The influence of charge on amino acid residue was explored by testing positively

charged AAC1-3, AAC5-7 and negatively charged AAC4. The impact of coumarin moiety

was investigated by comparing DAC-coupled dipeptides AAC2, AAC4 and AAC5 with

peptides containing benzyl succinate (AAC1) and benzyl amide (AAC3 and AAC7). A

dipeptide without aromatic moiety on the second lysine side chain AAC6 was also tested.

Scheme 2.1 Chemical structures and features of AAC1-7.

AAC1-7 were dissolved in phosphate-buffered saline (PBS, pH 7.4) solution at 20

mM for 1 day. Afterwards, the self-assembly of the peptide derivatives was investigated

46

by transmission electron microscopy (TEM). AAC1 formed several micrometer-long flat

nanoribbons with width of ~22 nm (Figure 2.4 a). AAC2 self-assembled into twisted

nanofibers with width of ~16 nm (Figure 2.4 b). AAC3 formed twisted nanoribbons with

widest width of 23 nm and narrowest width of 13 nm (Figure 2.4 c). AAC4 and AAC5 both

self-assembled into nanofibrils with width of 9 nm and 10 nm respectively (Figure 2.4 c,

d). AAC6 only formed amorphous aggregation (Figure 2.4 e) and AAC7 yielded coiled

nanoribbons with width of ~60 nm, some of which started wrapping into tubular structures

with diameter ranging from 60 to 70 nm (Figure 2.4 g).

47

Figure 2.4 TEM images of (a) AAC1, (b) AAC2, (c) AAC3, (d) AAC4, (e) AAC5, (f)

AAC6, (g) AAC7 in PBS (pH 7.4, 1 day) at 20 mM.

Short (6 h) and long-term (24 h) toxicity of AAC compounds on murine 3T3-L1

fibroblasts were investigated. Short-term experiments show that AAC3 was significantly

48

more cytotoxic compared to the other peptide derivatives, therefore it was excluded for

further experiments (Figure 2.5 a). AAC1 and AAC4-7 showed low but significant

cytotoxicity after 24 h (Figure 2.5 d), whereas cytotoxicity of AAC2 was unexpectedly low

that the cell viability of AAC2-treated cells was identical to control (Figure 2.5 d). Due to

the low cytotoxicity of AAC2, the effects of treating fibroblasts and human brain

endothelial cells with higher concentration of AAC2 were investigated for prolonged

period (Figure 2.5 b, c). After 24 h, the cell viability of AAC2-treated cells was still similar

to the control. Based on the preliminary experimental results, we suggested that AAC2 has

low cytotoxicity in both peripheral and braincells. Since the peptides were functionalized

with potential antioxidants such as coumarin, antioxidant properties of AAC1-7 were tested

under oxidative stress conditions induced by hydrogen peroxide (Figure 2.5 e). Only AAC6

showed reductive activity among all the AAC compounds. However, AAC6 had higher

cytotoxicity compare to AAC2. Thus, in following glycemic studies in vitro, both AAC2

and AAC6 will be tested.

49

Figure 2.5 (a) Cytotoxicity of 6 h-treatment without or with AAC1-3 (0.5, 100, and 500

µM) was measured in 3T3-L1 preadipocytes using lactate dehydrogenase (LDH) activity

assay. Cytotoxicity of (b) 3T3-L1 preadipocytes and (c) human brain endothelial cells

treated with different concentrations of AAC2 or left untreated for up to 72 h. (d)

Cytotoxicity of 3T3-L1 preadipocytes treated with AAC compounds (0.1 μM) or left

untreated for 24 h. (e) Reactive oxygen species concentration was measured in 3T3-L1

preadipocytes stimulated with H2O2 for 4 h (200 μM) and treated with and without AAC

(0.1μM) for 24 h.

50

Additionally, AAC2 was further studied due to its low cytotoxicity. The self-

assembly of AAC2 in PBS at pH 7.4 was investigated. After aging for 1 day at room

temperature, AAC2 was investigated by TEM. AAC2 self-assembled into twisted

nanofibers with widest width of 16 nm and narrowest width of 10 nm. According to the

results observed from TEM, each twisted nanofiber results from intertwining of

protofilaments with diameter of approximately 4 nm. (Figure 2.6 a). UV-Vis spectroscopy

(Figure 2.6 b) revealed that changing the solvent form trifluoroethanol (TFE) to PBS

resulted in decrease of intensity and blue-shift of λmax from 430 nm to 397 nm, indicating

that H-type aggregation was present with the DAC coumarin on AAC2.53 Circular

dichroism (CD) spectroscopy (Figure 2.6 c) exhibited exitonic couplet with zero-crossing

at ~415 nm, indicating M-type helical packing of DAC coumarin was present in the self-

assembled structure.53 Deconvolution of Fourier-transform Infrared (FT-IR) spectrum

(Figure 2.6 d) showed intense absorption at 1610 and 1635 cm-1 in the amide I region,

which is characteristic of -sheet structure. Minor absorption at 1650 cm-1 indicated that

there was small percentage of α-helix present in self-assembly.54, 55 Thioflavin T (ThT)

binding assay was also tested.56 Enhanced fluorescence intensity of ThT solution was

observed as more AAC2 samples were added (Figure 2.6 e), which indicates that AAC2

formed amyloid fibrils.57, 58

51

Figure 2.6 (a) TEM image of the self-assembled structure of AAC2 in PBS. (b) UV-Vis

spectra of AAC2 in TFE and PBS. (c) Co-plot of UV-Vis and CD spectra of AAC2 in

PBS. (d) FT-IR spectrum of AAC2. (e) Thioflavin T binding assay (Excitation: 440 nm

and Emission: 482 nm) of AAC2 in PBS (1 mM, aged for 24 h). (f) Plot of fluorescence

intensity of Nile Red at 656 nm (Ex = 550 nm) versus the concentration (mM) of AAC2

in PBS.

52

Since lysine side chain has pKa of 10.5,59 AAC2 should be positively charge under

physiological condition (pH 7.4). Insulin, with isoelectric point at pH 5.3,60 is negatively

charged at pH 7.4. Hence, the oppositely charged AAC2 and hINS should be able to bind

together via electrostatic attraction. Preliminary researches showed that incorporating

insulin with self-assembled nanostructures could prolong circulation life and control the

release of insulin in response to blood glucose change.25, 61 Therefore, human insulin

(hINS) was combined with self-assembled AAC2 and investigated. AAC2 was diluted

from 20 mM to 0.1 mM and titrated with hINS solution at different concentrations in 1:1

ratio by volume. Zeta potentials of AAC2-hINS mixtures were measured (Figure 2.7 a).

Titration result indicated that as concentration of hINS increased, zeta potential of AAC2-

insulin mixture dropped from 15 mV to -20 mV. Decreased zeta potential indicated that

the interface between self-assembly of AAC2 and solvent became more negative, meaning

negatively charged hINS molecules were bound to AAC2 nanofibers.

TEM was utilized to observe AAC2-hINS complex. To visualize insulin, gold

nanoparticle (GNP) functionalized with HS-PEG-COOH was coupled with amine tail of

hINS molecule.62 TEM image revealed that hINS bound to the surface of AAC2 (Figure

2.7 b). Quartz crystal microbalance with dissipation (QCM-D) binding assay was also

employed to investigate AAC2-hINS complex. The progressive decrease in frequency

signal (Figure 2.7 c) and increased thickness of AAC2 film after hINS addition (Figure 2.7

d) indicated that hINS was able to bind to AAC2 assembly.

53

Figure 2.7 a) Titration of AAC2 (0.1 mM in PBS, pH 7.4) with hINS at different

concentrations. b) TEM image of AAC2-hINS complex. c) Change in frequencies and

dissipations vs. time for hINS (10µg/mL) and AAC2 nanofiber (0.1µM) on active gold

surface. Insulin were introduced at t=500s. d) Values of thickness of AAC2 nanofiber

and hINS on the active gold surface in real time were calculated to unveil molecular

interaction between AAC2 nanofiber and insulin.

Critical micelle concentration (CMC) was measured using solvochromatic dye Nile

Red and the concentration was 84 µM (Figure 2.6 f). The CMC of AAC2 in PBS was 840

times higher than the concentration used for experiments in vitro. Thus, we considered that

AAC2 remained in monomeric form in this study. Based on preliminary experiment results,

54

AAC2 and AAC6 was chosen for glycemic studies in vitro due to their low cytotoxicity

and antioxidant activity respectively. The anti-diabetic efficacy of AAC2 and AAC6 was

first tested on the relevant primary human stromal vascular fraction preadipocytes (SVF),

which were isolated from visceral (omental) fat from obese patients served as an example

as peripheral tissue.63, 64 Administration of AAC2 showed a dose-dependent increase in

glucose uptake in SVF preadipocytes, whereas AAC6 reduced glucose uptake (Figure 2.8

a). Therefore, due to the efficacy of anti-diabetic activity and low cytotoxicity, AAC2 was

selected for further investigation.

The glucose uptake of AAC2 and human insulin (hINS) was compared using SVF

isolated from six patients. Treatment with AAC2 resulted in glucose uptake in all patients,

while hINS was effective on only 50% of the patients (Figure 2.8 b). Glycemic properties

of AAC2 in human brain endothelial cells (hBEC) were also investigated and AAC2 was

compared with hINS and leptin (hLep). Since hBEC cells primarily utilize glucose

transporter 1 (GLUT1) to facilitate glucose transport across the cell membrane,16 GLUT1

inhibitor was used to suppress glucose uptake of the cells. AAC2 and leptin induced

glucose uptake (Figure 2.8 c) and cells incubated with GLU1 inhibitor was not responsive

to AAC2 and leptin (Figure 2.7 d). hINS did not have any effect on hBEC cells (Figure 2.8

d). Mouse 3T3-L1 preadipocytes, which use glucose transporter 4 (GLUT4) as major

transporter and GLUT1 as minor transporter,65 was also tested. AAC2, leptin and hINS all

induced glucose uptake in mouse 3T3-L1 preadipocytes. Incubation of GLUT1 inhibitor

suppressed glucose uptake of cells administrated with AAC2 and leptin but not with hINS

(Figure 2.8e). Interestingly, AAC2 can induce glucose uptake in differentiated 3T3-L1

55

adipocytes. However, 3T3-L1 adipocytes were responsive to leptin and hINS (Figure 2.8

e), which was in concord with the insulin and leptin resistance observed in adipocytes. To

summarize, AAC2 and leptin induce glucose uptake using different glucose transporter

compare to insulin and AAC2 influenced glucose uptake in both peripheral adipocytes and

in endothelial cells of nervous tissue.

Figure 2.8 (a) Dose-dependent FD-glucose uptake in SVF cells stimulated with AAC2

and AAC6. (b) FD-glucose uptake in non-treated (Veh) SVF cells or stimulated with

AAC2, or hINS for 80min. (c) Glucose uptake in non-treated (Veh) 3T3-L1 adipocytes or

stimulated with hINS, mLep or AAC2. (d) FD-glucose uptake in human brain endothelial

cells (hBEC) treated with vehicle (Veh; PBS) or hINS, human leptin (hLep), or AAC2 in

the presence and absence of GLUT1 inhibitor. (e) FD-glucose uptake in mouse 3T3-L1

preadipocytes treated with vehicle (Veh;PBS) or hINS, mouse leptin (mLep), or AAC2 in

the presence and absence of GLUT1 inhibitor.

The mechanism of AAC2-mediated glucose uptake was investigated using 3T3-L1

preadipocytes. AAC2 increased glucose uptake in a concentration-dependent manner

(Figure 2.9 a). Both AAC2 and hINS induced glucose uptake in 3T3-L1 preadipocytes

56

(Figure 2.9 b). However. incubation of 3T3-L1 preadipocytes with anti-insulin receptor

(InsR) antibodies only interfered the glucose uptake stimulated by insulin (Figure 2.9 b).

To obtain profound understanding of the initial observation, AKT and PI3K pathways,

which mediate downstream effects of activated InsR in 3T3-L1 preadipocytes, were

investigated.66 Inhibition of AKT and PI3K pathways did not suppress glucose uptake in

3T3-L1 preadipocytes (Figure 2.9 c), which indicated that AAC2 induced glucose uptake

via different pathways. AMPK, MAPK, PPARα, EGFR and FGFR pathways were also

ruled out since inhibition of these pathways did not prevent glucose uptake in the cells

treated with AAC2 (Figure 2.9 d).

57

Figure 2.9 (a) Dose-dependence FD-glucose uptake stimulated by AAC2 in 3T3-L1

preadipocytes after 100 min of incubation. (b) FD-glucose uptake in non-stimulated

(Veh) or stimulated with AAC2 or hINS in 3T3-L1 cells for 80 min. Prior to stimulation

cells were incubated with Veh, heat-inactivated immunoglobulin (data not shown), or

anti-InsR antibody for 40 min. (c) FD-glucose uptake (% vs. Veh) in presence of AAC2

with and without PI3K inhibitor or pan-Akt inhibitor in 3T3-L1 preadipocytes. (d)

Glucose uptake in 3T3-L1 preadipocytes mediated by AAC2 with or without inhibitors

for various pathways implicated in glucose uptake.

Since glucose uptake in peripheral tissues can be regulated by leptin-leptin receptor

(LepR) pathway,67 glucose uptake mediated by AAC2 and leptin were compared in 3T3-

L1 preadipocytes. The cells were first incubated with inactivated or intact antibodies

against LepR, then treated with AAC2 or leptin. Inhibition of LepR suppressed glucose

uptake in 3T3-L1 preadipocytes, indicating that AAC2 and leptin mediate glucose uptake

via LepR (Figure 2.10 a). To consolidate this observation, glucose uptake mediated by

58

AAC2 and leptin were also measured in cells with genetically dysfunctional LepR (Figure

2.10 b). AAC2 and leptin were not able to induce glucose uptake in these cells, which

further confirmed that AAC2 and leptin regulate glucose homeostasis via LepR.

Figure 2.10 (a) FD-glucose uptake (% compared to Veh) in presence of AAC2 or

recombinant mouse leptin protein in 3T3-L1 preadipocytes incubated with inactivated

antibodies or poly clonal anti-LepR antibodies. (b) FD-glucose uptake (% compared to

Veh) in presence of AAC2 or recombinant mouse leptin protein in SVF cells isolated

from subcutaneous fat of Leprdb mouse.

The effects of AAC2, leptin and insulin on major signaling pathways in 3T3-L1

preadipocytes were examined to further understand the mechanism of glucose uptake

regulation mediated by AAC2. Expression of phosphorylated and non-phosphorylated

proteins in different pathways were investigated (Figure 2.11 a). Western blot results

showed that insulin treatment led to strong activation of AKT and weak activation of

mTOR, STAT3, STAT5, and ERK after 15 min treatment. Leptin treatment only activated

mTOR after 15 min. AAC2 only had weak effect on AKT, mTOR, STAT3 and STAT5,

but it activated ERK and PKCς. It was reported that PKCς can regulate glucose uptake in

response to mechanical stretch in muscle cells.68 Therefore, PKCς pathway activity was

investigated in AAC2-treated 3T3-L1 preadipocytes. ZIP inhibitor was used to suppress

59

PKCς activity in cells and it was observed that inhibition of PKCς interfered AAC2-

mediated glucose uptake in the cells (Figure 2.10 b), indicating that AAC2 regulated

glucose uptake via PKCς in a different manner compare to leptin.

Figure 2.11 (a) Expression of phosphorylated and non-phosphorylated proteins measured

in 3T3-L1 preadipocytes treated with leptin, insulin and AAC2 for 5 or 15minutes using

Western blot. (b) FD-glucose uptake (% compared to Control) in presence in the absence

(Veh) of AAC2 inhuman visceral SVF cells with and without ZIP inhibitor.

Preliminary experiment results indicated that AAC2 can regulate glucose uptake

via LepR. Thus, interaction between AAC2 and LepR was investigated and compared with

leptin-LepR interaction utilizing a quartz crystal microbalance. Binding of LepR on the

active gold surface increased the dissipation and decreased the frequencies. Binding of

leptin with LepR resulted in further increased the dissipation and decreased the frequencies

(Figure 2.12 a), which indicated a thin film of leptin was formed on the active gold surface.

On the contrary, addition of AAC2 resulted in decreased dissipation and increased

frequencies (Figure 2.12 b), meaning that LepR was dissociated from the active gold

60

surface. The decrease in LepR film thickness after addition of AAC2 also validated the

deduction (Figure 2.12 c). The quartz crystal microbalance showed that AAC2 had strong

interaction with LepR and it was distinctive compare to that of leptin-LepR.

Figure 2.12 Binding affinity between recombinant mouse leptin receptor protein (LepR)

and leptin (a) or binding affinity between LepR and AAC2 (b); Blue line shows

frequency and orange line shows dissipation. (c) Thickness of LepR-leptin film or LepR-

AAC2 film.

The effects of AAC2 in vivo were examined on LepR deficient Leprdb mice. The

mice were administrated with AAC2 for one month. Glucose tolerance test (GTT) showed

that glucose uptake in Leprdb mice was impaired by AAC2 (Figure 2.13 a). Food intake,

weight gain and insulin level were not affected by AAC2 either (Figure 2.13 b, c, d). On

the contrary, AAC2 treatment on leptin deficient Lepob mice resulted in improved glucose

uptake (Figure 2.13 e). Even though the food intake of AAC2-treated deficient Lepob mice

was decreased compare to the control group (Figure 2.13 f), the weight gain of AAC2-

treated deficient Lepob mice was significantly lower than the control group (Figure 2.13 g).

The experiment results indicated that AAC2 can regulate glucose homeostasis in vivo. The

process did not require leptin but LepR must be present. The result was also in agreement

61

with binding studies results of AAC2 and LepR. AAC2 mediates glycemic effect in vivo

via LepR, while it did not fully function like leptin.

Figure 2.13 (a) GTT in Leprdb mice treated without (Veh) or with AAC2. (b) Food intake

in Leprdb mice treated without (Veh)or withAAC2. (c) Weight gain in Leprdb mice treated

without (Veh) or with AAC2. (d) Insulin levels in plasma of Leprdb mice. (e) GTT in

Lepob mice treated without (Veh) or with AAC2. (f) Food intake in Lepob mice treated

without (Veh) or withAAC2. (g) Weight gain in Lepob mice treated without (Veh) or with

AAC2. (h) Insulin levels in plasma of Lepob mice.

AAC2 was also tested on type 1diabetic (T1D) Ins2Aktia mice. The mice were

administrated with AAC2 or insulin every 48 h for 4 weeks. Before treatment, all three

groups of mice had severe hyperglycemia (Figure 2.14 a). After 4-week treatment, the

insulin level in control group and AAC2-treated group were similar and significantly lower

62

than the insulin-treated group (Figure 2.13 b). Interestingly, food intake and water

consumption of AAC2-treated mice were higher than insulin-treated mice and control

group (Figure 2.14 c, d). These phenomena were in agreement with preliminary studies

which showed regulation of food intake and water consumption were related to the

activation of LepR in hypothalamus.69, 70 All three groups showed a respiratory exchange

ratio (RER) higher than 0.8 during active dark and light day cycles (Figure 2.14 e, f),

indicating that glucose was the predominant energy substrate. GTT results demonstrated

that the control group was severely glucose tolerant. Whereas AAC2- and insulin-treated

groups showed improved glucose uptake (Figure 2.14 g). Overall, AAC2 exhibited high

efficacy similar to hINS in glucose homeostasis regulation in genetic mouse model of T1D.

63

Figure 2.14 (a) Baseline fasting glucose levels prior to treatment in Ins2Akita mice. (b)

Mouse insulin levels measured in same Ins2Akita mice at the end of the study. (c) Food

and (d) water consumption measured in same Ins2Akita mice 7 weeks after treatment.

Respiratory exchange ratio (RER) measured in same Ins2Akita mice during the (e) dark

and (f) light period. (g)GTT in same Ins2Akita mice 3weeks after beginning of treatment.

Both AAC2 and hINS regulated glucose uptake in Ins2Aktia mice. However, they

had different effects on body composition of the mice. All three groups of mice had similar

weight at the end of the studies (Figure 2.15 a), but the body fat proportion in insulin-

64

treated mice was 172% higher than the AAC2-treated mice and the control group (Figure

2.15 b), which contradicted the observation of decreased food consumption in insulin-

treated mice (Figure 2.15 c). The paradoxical phenomenon could be explained by the

lipogenesis activity induced by insulin.3, 4 In addition, AAC2-treated mice had similar body

composition of fat and lean mass to the control group (Figure 2.15 c).

Figure 2.15 (a) Body weight in Ins2Aktia mice. (b) Percent body fat in Ins2Aktia mice. (c)

Percent lean body mass in Ins2Aktia mice.

The brain mass of AAC2-treated mice was significantly higher than the control

group (2.16 a). To understand whether the behaviors and the cognitive performance were

related to the changes in brain mass, behavioral open field tests were performed on the

Ins2Aktia mice. 71 Distance traveled in the light compartment and amount of time in

periphery were much shorter in AAC2-treated mice (Figure 2.16 b, c) compare to the

control group. AAC2-treated mice showed reduced number of rears (Figure 2.16 d),

indicating low anxiety level. Barnes maze test was used to estimate the cognitive

performance of the mice.72 AAC2-treated group show significantly shorter latency period

(27 s) compare to the control group (63 s). The latency period of insulin-treated group was

65

35.9 s, which was not statistically significant (Figure 2.16 e). The errors made by the mice

during a 5-day training period in the test were measured. All three groups made similar

amount of errors by the end of the training period (Figure 2.16 f). At day 6, a probe test

was run to assess the acquisition and retention of the spatial reference memory in the mice

and all group show similar responses. To summarize, the cognitive performance was

moderately improved by AAC2 or hINS treatment in Ins2Aktia mice.

Figure 2.16 (a) Brain mass in Ins2Aktia mice. (b) Total movement distance, (c) Amount of

activity in the periphery of the arena and (d) number of rears were conducted using open

field test. (e) Latency time and (f) number of errors measured in the training period. (g)

Hole escape time at day6 (Q3 in same experiment).

66

Conclusion

A series of peptide derivatives AAC1-7 which contained amino acids with different

charges and antioxidative moieties, were synthesized and investigated. Among the all the

AACs, AAC2 showed promising effect on controlling glucose homeostasis in 3T3-L1

preadipocytes and human brain endothelial cells by activating GLUT1. Furthermore,

AAC2 activated LepR and PKCς to increase glucose uptake in vitro. Animal studies

revealed that AAC2 did not induce glucose uptake in leptin receptor deficient Leprdb mice,

whereas in leptin deficient Lepob mice. In type 1 diabetic Ins2Akita mice, AAC2 maintained

glucose homeostasis as insulin without increasing adiposity. AAC2 also increased brain

mass and anxiety-related behaviors in Ins2Akita mice. Overall, AAC2 induced glucose

uptake via a distinct mechanism that activated LepR/PKCς/GLUT1 axis and it could

provide a novel strategy to treat diabetes and prevent complications of nervous and insulin-

resistant tissues.

2.3 Experimental Section

Syntheses of Starting Materials

Benzyl alcohol (12.67 g, 126.7 mmol) and succinic anhydride (10.0 g, 92.4 mmol) were

added to dichloromethane and DMAP (2.26 g, 18.5 mmol) was later added. The mixture

was reacted at room temperature for 12 hours and the crude product was extracted by

adding saturated Na2CO3 aqueous solution. The aqueous layer of the mixture was collected,

and the pH was adjusted to 2. Afterwards, the solution was extracted by dichloromethane.

67

The organic layer was collected and dried with Na2SO4. The solvent was then removed

under vacuum and the product was yield as a white solid without further purification (16.53

g, 86%).73

Scheme 2.2 Synthesis of benzyl succinic acid.

4-Diethylaminosalicylaldehyde (3.86 g, 20 mmol), diethylmalonate (6.40 g, 40 mmol) and

piperidine (2 mL) were combined in absolute ethanol (60 mL) and stirred for 6 h at reflux.

Then 10% NaOH (60mL) aqueous solution was added to the mixture and the solution was

heated at reflux for 15 minutes. The reaction mixture was cooled down to room temperature

and the pH of the mixture was adjusted to 2 with concentrated hydrochloric acid to obtain

an orange precipitate. The crude product was filtered, washed with cold water and

recrystallized into orange crystal in absolute ethanol (4.17g, 80%).74

Scheme 2.3 Synthesis of DAC.

General Peptide Preparation

The peptide is synthesized using a solid phase peptide coupling protocol on Rink

amide resin (0.8 g/mmol). All amino acids were coupled using Fmoc-protected amino

acids, DIC and HOBt, which were combined in DMF and reacted for 2 h. The Fmoc group

was removed using 20% piperidine in DMF and the Mtt group was deprotected using

68

TFA/TES/DCM (2:1:97). Boc, tBu and Pbf groups were removed using TFA/TES/H2O

(94:5:1) at the final cleaving step. Benzyl succinic acid, DAC and benzoic acid were

coupled on the deprotected lysine side chain using HOBt, HBTU and DIPEA to yield

AAC1-7 respectively. The final peptides were cleaved with TFA/TES/H2O (94:5:1). After

cleavage from the solid support, all AAC peptides were purified by high performance

liquid chromatography. AAC structures were validated using 1HNMR and13CNMR and

mass spectroscopy.

Scheme 2.4 Synthesis of AAC1.

AAC1 1H NMR (700 MHz, DMSO-d6) δ 7.90 (2H, d, J=7.5 Hz), 7.82 (1H, t, J=5.5 Hz),

7.80 (1H, d, J=8.0 Hz), 7.73 (1H, d, J=7.5 Hz), 7.71(1H, d, J=7.5 Hz), 7.64 (2H, bs),

7.51(1H, d, J=8.1 Hz), 7.42(2H, t, J=7.4 Hz), 7.28-7.39 (8H, m), 7.02 (1H,s), 5.07 (2H,s),

4.29 (2H, m), 4.23 (1H, t, J=7.07 Hz), 4.18 (1H, m), 4.00 (1H, m), 2.99 (2H, m), 2.76 (2H,

m), 2.55 (2H, t, J=6.9 Hz), 2.36 (2H, t, J=6.9 Hz), 1.64 (2H, m), 1.52 (4H, m), 1.21-1.39

69

(6H, m); 13C NMR (176 MHz, DMSO-d6) δ 173.98, 172.73, 172.04, 170.85, 156.45,

144.37, 144.19, 141.20, 136.70, 128.86, 128,40, 128.26, 128.12, 127.56, 127.54, 125.76,

125.71, 120.61, 120.60, 66.08, 65.83, 54.89, 52.58, 47.14, 39.19, 38.92, 32.31, 31.71,

30.27, 29.52, 29.31, 27.03, 23.11, 22.80; ESI-MS for C38H47N5O7 [M+H]+ calculated

686.3548; found 686.3567.


AAC2 1H NMR (700 MHz, DMSO-d6) δ 8.63 (1H, s), 7.87 (2H, d, J=7.5 Hz), 7.85 (1H,

d, J=8.0 Hz), 7.77 (3H, bs), 7.73 (1H, d, J=7.5 Hz), 7.70 (1H, d, J=7.4 Hz), 7.65 (1H, d,

J=9.0 Hz), 7.52 (1H, d, J=8.1 Hz), 7.41 (2H, t, J=7.2 Hz), 7.33 (2H, t, J=7.4 Hz), 7.04 (s,

1H), 6.79 (1H, dd, J=9.0, 2.2 Hz), 6.58 (1H, d, J=2.0 Hz), 4.29 (2H, m), 4.21 (2H, m), 4.01

(1H, m), 3.46 (4H, m), 3.27 (2H, m), 2.77 (2H, m), 1.67 (2H, m), 1.48-1.59 (6H, m), 1.33

(4H, m),1.13 (6H, t, J=7.0 Hz); 13C NMR (176MHz, DMSO-d6) δ 174.03, 172.08, 162.56,

70

162.25, 157.65, 156.45, 152.84, 144.39, 144.18, 141.18, 131.98, 127.54, 127.52, 125.76,

125.70, 120.55, 110.56, 109.90, 108.11, 96.28, 66.07, 54.94, 52.56, 47.14, 44.78, 39.28,

39.15, 32.31, 31.70, 29.35, 27.02, 23.20, 22.80, 12.74; ESI-MS for C41H50N6O7 [M+H]+

calculated 739.3814; found 739.3818.


AAC3 1H NMR (700 MHz, DMSO-d6) δ 8.48 (1H, t, J=5.5 Hz), 8.01 (1H, d, J=8.1 Hz),

7.99 (1H, d, J=8.1 Hz), 7.94 (1H, d, J=8.0 Hz), 7.91 (2H, d, J=7.6 Hz), 7.84 (2H, d, J=7.14

Hz), 7.72 (1H, d, J=7.3 Hz), 7.71(1H, d, J=7.0 Hz), 7.68 (2H, bs), 7.63 (2H, bs), 7.51 (1H,

t, J=7.4 Hz ), 7.50 (1H, d, J=8.1Hz), 7.44 (2H, t, J=7.9 Hz), 7.42 (2H, t, J=7.5 Hz), 7.33

(2H, t, J=7.5 Hz), 7.20-7.25 (5H, m), 7.18 (1H, t, J=6.8 Hz), 7.05 (1H, s), 4.54 (1H, m),

4.30 (1H, m), 4.23 (3H, m), 4.16 (1H, m), 3.98 (1H, m), 3.25 (2H, m), 3.05 (1H, m), 2.68-

71

2.83 (5H, m), 1.70 (1H, m), 1.44-1.63 (12H, m), 1.23-1.33 (6H, m); 13C NMR (176MHz,

DMSO-d6) δ 173.85, 172.30, 171.80, 171.09, 166.65, 156.48, 144.29, 144.26, 141.20,

138.05, 135.09, 131.51, 129.63, 128.70, 128.50, 128.14, 127.60, 127.54, 126.72, 125.77,

125.73, 120.65, 120.61, 66.06, 54.78, 54.22, 52.89, 52.65, 47.12, 39.19, 37.80, 32.38,

31.98, 31.71, 29.40, 27.10, 23.27, 22.98, 22.55; ESI-MS for C49H62N8O7 [M+H]+



AAC4 1H NMR (700 MHz, DMSO-d6) δ 8.64 (1H, s), 8.62(1H, t, J=5.7 Hz), 7.88 (2H, d,

J=7.5 Hz), 7.83 (1H, d, J=8.0 Hz), 7.73 (1H, d, J=7.5 Hz), 7.71 (1H, d, J=7.5 Hz), 7.67

(1H, d, J=9.0 Hz), 7.57 (1H, d, J=8.1 Hz), 7.41 (2H, t, J=7.4 Hz), 7.37 (1H, s), 7.33 (2H,

d, J=7.4 Hz), 7.02 (1H, s), 6.79 (1H, dd, J=9.0, 2.2 Hz), 6.60 (1H, d, J=2.1 Hz), 4.26 (2H,

m), 4.19 (2H, m), 4.02 (1H, m), 3.46 (5H, m), 3.26 (2H, m), 2.27 (2H, t, J=7.9 Hz), 1.92

72

(1H, m), 1.76 (1H, m), 1.68 (1H, m), 1.56 (1H, m), 1.50 (2H, m), 1.31 (2H, m), 1.14 (6H,

t, J=7.0 Hz); 13C NMR (176MHz, DMSO-d6) δ 174.43, 173.90, 171.65, 162.53, 162.24,

157.65, 156.39, 152.84, 148.10, 144.38, 144.20, 141.16, 132.00, 128.09, 127.55, 125.79,

125.76, 120.55, 110.57, 109.95, 108.13, 96.32, 66.15, 54.44, 52.58, 47.11, 44.78, 39.25,

32.25, 30.70, 29.35, 27.75, 23.18, 12.78; ESI-MS for C40H45N5O9 [M+23]+ calculated

762.3109; found 762.3107.


AAC5 1H NMR (700 MHz, DMSO-d6) δ 8.64 (1H, s), 7.89 (2H, t, J=7.6 Hz), 7.83 (1H, d,

J=8.0 Hz), 7.73 (1H, d, J=7.5 Hz), 7.70 (1H, d, J=7.5 Hz), 7.67 (1H, d, J=9.1 Hz), 7.57

(1H, d, J=8.2 Hz), 7.52 (1H, t, J=5.5 Hz), 7.41 (2H, t, J=7.4 Hz), 7.32 (2H, t, J=7.4 Hz),

7.04 (1H, s), 6.80 (1H, dd, J=9.0, 2.3 Hz), 6.59 (1H, d, J=2.2 Hz), 4.29 (2H, m), 4.22 (2H,

73

m), 4.04 (1H, m), 3.48 (4H, m), 3.37 (2H, m), 3.10 (2H, m), 1.67-1.72 (2H, m), 1.44-1.60

(6H, m), 1.26-1.35 (2H, m), 1.14 (6H, t, J=7.1 Hz); 13C NMR (176MHz, DMSO-d6) δ

173.90, 171.80, 162.56, 157.66, 157.13, 156.40, 152.87, 144.38, 144.15, 141.18, 132.01,

128.10, 127.55, 125.70, 120.57, 110.60, 109.98, 108.12, 96.30, 66.12, 54.76, 52.54, 47.13,

44.79, 40.91, 39.29, 32.35, 29.54, 29.36, 25.56, 23.13, 12.77; C41H50N8O7 [M+H]+



AAC6 1H NMR (700 MHz, DMSO-d6) δ 7.91 (2H, d, J=7.4 Hz), 7.72 (2H, d, J=6.4 Hz),

7.50 (1H, d, J=8.0 Hz), 7.43 (2H,t, J=7.5 Hz), 7.38 (1H, s), 7.34 (2H, t, J=7.4 Hz), 7.04

(1H,s), 4.14-4.32 (4H, m), 4.00 (1H, m), 2.75 (4H, m), 1.65 (2H, m), 1.49-1.59 (6H, m),

1.31 (4H, m); 13C NMR (176MHz, DMSO-d6) δ 173.81, 172.19, 156.47, 144.31, 144.25,

141.20, 128.14, 127.55, 125.77, 125.75, 120.64, 120.61, 66.07, 54.87, 52.42, 47.13, 39.17,

32.02, 31.67, 27.12, 27.06, 22.89, 22.65; ESI-MS for C27H37N5O4 [M+H]+ calculated

496.2918; found 496.2922.

74


AAC7 1H NMR (700 MHz, DMSO-d6) δ 8.42 (1H, t, J=5.9 Hz), 7.90 (2H, d, J=7.1Hz),


Hz), 7.50 (1H, d, J=7.3 Hz), 7.40-7.46 (5H, m), 7.38 (1H, s), 7.33 (2H, t, J=7.4Hz), 7.03

(1H, s), 4.28 (2H, m), 4.22 (2H, m), 4.00 (1H, m), 3.23 (2H, m), 2.76 (2H, m), 1.62-1.72

(2H, m), 1.47-1.59 (7H, m), 1.27-1.37 (5H,m); 13C NMR (176MHz, DMSO-d6) δ 173.98,

172.04, 166.55, 156.45, 144.38, 144.20, 141.20, 135.15, 131.46, 128.88, 128.12, 127.57,

125.76, 125.72, 120.62, 120.60, 120.51, 66.08, 54.89, 52.63, 47.14, 40.50, 39.24, 32.43,

31.75, 29.37, 27.11, 23.24, 22.79; ESI-MS for C34H41N5O5 [M+H]+ calculated 600.3180;

found 600.3189.

Circular Dichroism (CD) Spectroscopy Measurement.

CD spectra were recorded on a Jasco CD J-815 spectrometer under nitrogen atmosphere.

Experiments were performed in a quartz cell with a 1 mm path length over the range of

75

190-600 nm. Samples were prepared as 20mM solution in PBS after 1-day incubation at

room temperature, and subsequently diluted to 1mM before the measurement.

Thioflavin T (ThT) Assay

ThT stock solution was prepared (8mg in 10mL PBS, pH 7.4). The stock solution was

diluted 50x to yield the working solution. An aliquot (10µL) of AAC2 was added to 0.2mL

of working solution each time and fluorescence intensity was measured in a 3mm quartz

cuvette. (Excitation: 440 nm, slit width:1.5; Emission: 482 nm, slit width: 3).56

Fourier Transform Infrared (FT-IR) Spectroscopy Measurement

FT-IR spectra were collected on a Shimadzu FTIR spectrometer at ambient temperature.

Spectra were recorded between 1700 and 1600 cm-1 at a resolution of 4 cm-1, and a total

of 128 scans were averaged. Samples for FT-IR were first dissolved in PBS (20mM) and

freeze-dried to remove water. The sample was re-dissolved in D2O for FT-IR measurement.

Spectra were analyzed in a transmission cell having CaF2 windows and a 0.025 μm path

length. After subtracting the solvent spectrum from the sample spectrum, the amide I band

(1600-1700 cm-1) of each spectrum was analyzed using peak fit with Gaussian method on

Origin.

Transmission Electron Microscopy Measurement

AAC1-AAC7 were dissolved in PBS to form 20mM solution and left to self-assemble for

12h. After gelation, the solution was diluted to1mM and 30 μL diluted samples were loaded

on the formvar/carbon-covered copper grid and stained with uranyl acetate (2 wt% in

distilled water) for 30s and the grids were dried with filter paper. The nanostructures of the

AAC1-AAC7 were observed by TEM.

76

Zeta Potential Measurement

AAC 2 (0.1mM in PBS, pH 7.4) was combined with insulin solution in concentrations

ranging from 5 ng/mL to 10 mg/mL in 1:1 ratio by volume. The AAC 2/insulin samples

were set at 2 °C for 4 h and then taken out for zeta potential measurement. The zeta

potentials of the AAC 2/insulin samples were measured with the folded capillary zeta cell.

Conjugation of Gold Nanoparticle and Insulin

5 nm gold nanoparticle (100 µL, 0.25% wt) functionalized with HS-PEG-COOH was

coupled with hINS (200 µL, 1 mg/mL) using 1-ethyl-3-(3-

dimethylaminopropyl)carbodiimide (EDC) and N-hydroxysuccinimide (NHS). The crude

product was centrifuged at 6000 rpm for 30 min. The pellet was then resuspended with

PBS (pH 7.4).

Critical micelle concentration of AAC2 with Nile Red

AAC2 samples were prepared by serial dilution starting from 2.5mM in PBS with no aging.

Nile Red (4.24μM) was added and the solution was incubated for an additional 24 h.

Fluorescence measurements were taken at excitation/emission550nm/ 656 nm, in a 3 mm

quartz cuvette, slit widths 5.

Quartz crystal microbalance with dissipation (QCM-D) binding assay

Interaction of either AAC2 (0.1μMin PBS) or mouse recombinant leptin protein

(mLep;1.6fMinPBS) and with mouse recombinant leptin receptor (LepR) protein (1.6 pM

in PBS) were investigated by applying an alternating current on quartz via the piezoelectric

effect using QCM-D.75, 76 Quartz sensor with an active gold surface was used. The

77

interaction of each component layer, measured as difference in frequency (ΔF) and

dissipation (ΔD) values of the odd overtones was modeled using Voight Voinova equations

for homogenous viscoelastic layers.77, 78

Cytotoxicity test (WST-1 assay)

3T3-L1 preadipocytes were seeded into 48-well plates (5 × 104 per well). Then, after 24 h,

cells were treated with 0.1μM AAC for 24h in DMEM containing 10% calf serum. After

incubation, 10 μl of WST-1 solution was added directly into themedia (1:10ratio) and

incubated for 3 h. After incubation, absorbance was measured at 450 nm using Synergy H1

Hybrid Multi-Mode Microplate Reader. Similar experiments were performed using

different concentrations of AAC2 for 24 and 72 h in 3T3-L1 preadipocytes and hBEC

cultures.

Detection of reactive oxygen species (ROS)

ROS species production were detected using fluorescent CellROX Green Reagent

according to manufacturer's instructions. 3T3-L1 preadipocyte cells were seeded into 48-

well plates (5 × 104 per well) and treated with 200 μM H2O2 for 4 h to induce cellular ROS

production. After oxidative stress induction, these cells were treated with AACs (0.1μM

each) and incubated for additional 24 h. Then, 5 μM CellROX Green Reagent was used to

stain live cell ROS accumulation by measuring absorption/emission maxima at 485/520

nm using fluorescence microscope. Quantification of ROS positive area was analyzed by

ImageJ software (version1.8.0_112).

78

Glucose uptake assay

General protocol. Glucose uptake was measured using fluorescent2-deoxy-2-[(7-nitro-

2,1,3-benzoxadiazol-4yl)amino]-D-glucose) (2-NBDG or FD glucose). For all experiments

we used monolayer of cells. Cells were washed with PBS to remove residual glucose.

Starvation conditions were induced in the DMEM medium, which does not contain glucose

phenol red, and L-glutamine (200μL/well) for 40min otherwise described. The FD-

working solution (0.29 mM) was prepared in the glucose-free medium. After treatment,

cells were incubated with the FD-working solution containing reagents at 37°C for 80 min

otherwise described. Cells were washed with PBS twice. Then, the fluorescence of cells

was measured in cells containing 100μL of PBS per well at an excitation/emission

wavelength of 485/535 nm using Synergy H1 Hybrid Multi-Mode Microplate Reader. The

specifics of experimental conditions for each cell type are described below. Human SVF

were obtained from each donor and seeded at ~80% confluence on a flat-96 well plate in

the 100 μL/well of PGM-2 Preadipocyte Growth Medium-2 Bullet Kit.

After3days,glucoseuptake was measured in confluent cells.The starved cells were

stimulated with vehicle (Veh; PBS), AAC2 (1, 3, 10, 30, and 100 nM for Figure 2.7 a; 0.03

μM for Figure 2.7 b) or AAC6 (1, 3, 10, 30, and 100 nM for Figure 2.7 a), or human insulin

(hINS, 1.7 μM) that were added into 100μL of FD-working solution per well.

Experiment with PKCς inhibitor

Human visceral SVF cells were incubated with the ZIP inhibitor of acatalytic domain of

PKCς, which also exists as constitutively active form, i.e. protein kinase Mς [56] (1 μM)

79

or diluted in water or in glucose-free medium for 40 min. Then cells were incubated with

Veh or AAC2(0.1μM) inFD-working solution for 80min.

Experiments with GLUT 1inhibitor

hBEC were split and seeded onto a 96-wellplate (2×104/0.1mL/well) coated with 0.1%

gelatin solution. After ~24h, cells formed monolayer, then glucose uptake was performed.

Cells were treated with vehicle (Veh; PBS) or human insulin (hINS; 1.7 μM) or human

leptin (hLep; 62.5 nM,) or AAC2 (0.1 μM) which were diluted in same glucose free DMEM

(200 μL/well) for 40 min. Then, GLUT1 inhibitor ((BAY-876; 10 nM diluted in DMSO)

or DMSO were added in 100 μL of FD-working solution per well and incubated for 50 min

at 37 °C. 3T3-L1 preadipocytes were seeded in a 96 well plate at a density of 4 × 103 in

100 μL of culture medium per well and grow for 24 h prior to measurement of glucose

uptake. Cells were pre-incubated with GLUT1 inhibitor (BAY-876;10nM diluted in

DMSO) or DMSO diluted in DMEM not containing glucose phenol red, and L-glutamine

(200μL/well) fo r40min. Then, Vehor AAC2 (0.1μM) or human insulin (hINS;1.7μM) or

mouse leptin (mLep;12.5nM) were treated to cells with FD working solution for 80min.

Experiment with diverse AAC2 doses

3T3-L1cells were starved with glucose-free DMEM for 50 min. Then cells were treated

with FD-glucose solution containing vehicle or AAC2 (10, 100, and 300 nM) for 100min.

Experiment with anti-insulin receptor (InsR) antibody. 3T3-L1 cells were treated with heat-

inactivated immunoglobulin or anti-InsR antibody (2.96 pM) in glucose-free DMEM. After

80

40 min incubation, cells were stimulated with Vehor AAC2 (0.1μM) or human insulin

(hINS;1.7μM) diluted in the FD-working solution for 80min. Experiment with PI3K and

Akt inhibitors. 3T3-L1 cells were stimulated with FD-working solution containing AAC2

(0.1 μM), PI3K inhibitor (Wortmannin,0.1μM), pan-Aktinhibitor (GSK690693, 0.1 μM),

or no reagents (Veh control) for 80min.

Experiment with anti-leptin receptor (LepR) antibody

3T3-L1 cells were treated with heat-inactivated immunoglobulin or anti-LepR antibody

(3.2 pM) in the glucose-free DMEM (200μL/well). After 40 min incubation, cells were

stimulated with Veh or AAC2 (0.1μM) or mouse leptin (mLep;1.6fMinPBS) in the FD-

working solution for 80 min. Similar experiment was performed using wild type

subcutaneous SVF cells. Subcutaneous mouse Leprdb SVF cells were seeded in a flat 96-

well plate and grown in high glucose DMEM containing 10% FBS and 1% Penicillin-

Streptomycin (10,000 U/mL) for 1 week. Cells were stimulated with FD working solution

containing Veh or AAC2 (0.1 μM), or mouse leptin (mLep; 12.5nM) for 80min.

Western blot

Treated 3T3-L1 cells lysed using RIPA buffer, containing Halt™ Protease and Phosphatase

Inhibitor Cocktail (100X). Antibodies were purchased from Cell Signaling Technology:

protein kinase B (PKB, alias: AKT, 4691S), phosphorylated (p-)p-AKT (9271S), signal

transducer and activator of transcription 5 (STAT5, 94205S), p-STAT5 (4322S), STAT3

81

(9139S), the extracellular-signal-regulated kinase (ERK, 4696S), and p-ERK, (4370S). β-

Actin was purchased from Sigma-Aldrich (A5441).

Protein concentrations measurement

Protein concentrations were measured using Pierce BCA protein assay.

Enzyme-linked immunosorbent assay (ELISA)

The level of mouse insulin was measured in mouse plasma by ELISA following the

manufacturer's instruction. The absorbance at 450 and 590nm were measured using

SynergyH1 Hybrid Multi-Mode Microplate Reader.

Glucose tolerance test (GTT)

GTT test wasperformedforallstudiesusing4–5hfastedmiceafter 3-week treatment period.

Mice were i.p. injected with 10 % glucose solution (w/v;0.56M, diluted in distilled water

and sterilized,10μL/gBW). Glucose levels in tail-tip blood were measured using

glucometer during GTT experiments and weekly monitoring of glucose status.

Body composition measurement

Mouse body composition was measured with Echo MRI™-100H Body Composition

Analyzer for Live Small Animals 4 weeks after treatment.

82

Comprehensive Lab animal monitoring system (CLAMS)

Metabolic parameters were measured by indirect calorimetry at an ambient temperature

(22 °C) with 12 h light/dark cycles 7 weeks after treatment. Animals were fed the same

diet and water provided ad libitum and consumption was measured. Mice were placed

individually and metabolic parameters were measured for 24h.

Open field test

The open filed test was performed at the Behavioral Core facility at OSU in blinded fashion

using encoded groups of mice 5 weeks after treatment. Each animal is placed in a

polypropylene open-field arena (36 cm×36 cm) with two rows of infrared sensors mounted

on the sides to detect and distinguish between horizontal movements and vertical

movements (Open Field Photo beam Activity System).The arenas are contained in boxes

that are light- and sound-attenuating. Activity counts are defined as interruptions in the

infrared light sources by the animal (i.e., beam breaks). Total activity, amount of activity

in the center versus the periphery of th earena, and number of rears is analyzed.

Barnes maze test

Barnes maze was performed as described.72 The Barnes maze, (122 cm diameter) with 18

escape holes (9.5 cm) placed every 20° around the perimeter was surrounded with a 60 cm

high white polycarbonate barrier to prevent escape. The blind escape holes were blocked

by black panels, and the target escape hole was visually the same as the blind holes, but

contained a black escape box (38.7×12.1×14.2cm).Distinct visual cues (black 2

83

dimensional geometric shapes, 20–25 cm) on the upper edge were attached to of the

surround at the 4 compass points and present visual cues distal to the maze. Testing

consisted of 5 days of acquisition training followed by a single probe trial 24 h after the

last training trial. Each acquisition day consisted of one session/animal, 3 trials per session,

with an inter-trialintervalof5min. For acquisition training, all mice were allowed to

acclimate for 30 min before the start of testing. Each trial consisted of carefully placing the

mouse in the center of the maze from the opaque plastic beaker. The mouse was allowed

to search for the escape box for 120s, then it was guided to it. Olfactory cues were

eliminated by cleaning with 70% ethanol after testing of each mouse, and each day the

maze was rotated 90°counterclockwise, with the escape box location and location of visual

cues remaining constant throughout testing. All behavior on coded mice were recorded and

scored using The Observer software (XT8.0; Noldus). For training trials, latency to escape

and number of errors were recorded. An error was defined as an investigation of a blind

escape hole where the entire head of the mouse broke the plane of the edge of the escape

hole. For the probe trial, latency to escape hole, number of errors, and time in quadrant of

escape hole (% in path Q3) were measured.

Statistical analysis

All data were analyzed using SPSS23. All data are shown as mean ± standard error (SEM).

Number of samples for each assay is indicated in Figure legends. Group comparisons were

assessed using Student's independent or paired t-test(two-sided) or one-way analysis of

variance (ANOVA) for normally distributed samples. Mann-Whitney Utestor Kruskal-

84

Wallis test were used as nonparametric tests. P < 0.05 was considered statistically

significant.

Cells models

Human visceral stromal vascular fraction (SVF) cells Institutional review board–approved

informed consent was obtained for the patients' medical records. Human visceral fat tissues

(VF) were obtained from the greater omentum during endoscopic repair of hernias and/or

bariatric surgeries (laparoscopic banding and gastric bypass) from overnight fasted in

patients. Stromal vascular fraction cells (SVF) were isolated from VF using type1

collagenase.79 Isolated cells were cultured in PGM-2 Preadipocyte Growth Medium-2

Bullet Kit (supplemented withPT-9502). The medium was changed every 3 days prior to

measurement of glucose uptake.

Human brain endothelial cells (hBEC) Human BEC were grown with DMEM: F12

(ATCC, 30–2006) supplemented with 10% FBS and endothelial cell growth supplement.

Mouse subcutaneous SVF cells SVF cells were isolated from subcutaneous fat isolated

from Lepr deficient mice (Homozygous for Leprdb; 12-week old) or wild type male

(C56BL6/J) using type 1 collagenase following manufacture's instruction. The

subcutaneous SVF cells were seeded in a flat 96-well plate in 100 μL/well of high glucose

DMEM supplemented with 10% FBS and 1% Penicillin-Streptomycin (10,000U/mL).

Medium was changed every 48h.

Mouse 3T3-L1 cells Mouse 3T3-L1 fibroblast (preadipocyte) cells line were purchased

from ATCC (CL-173). The 3T3-L1 preadipocytes were maintained in high glucose DMEM

85

containing10 % newborn calf serum and 1% Penicillin-Streptomycin (10,000 U/mL).

Medium was changed every 48 h. Differentiation was initiated with medium containing

10% FBS, 1.7 μM bovine, 1 μM dexamethasone, 0.5 mM 3-isobutyl-1-methyl xanthine.

Medium was replaced every 48 h with DMEM containing 10% FBS, 10μg/mL insulin, and

continued for 6 days.

Animal study models

Animal studies were approved by the Institutional Animal Care and Use Committee of The

Ohio State University (OSU). All mice were purchased from The Jackson Laboratory and

were fed a regular chow diet (Teklad LM-485mouse/rat diet, irradiated) under 12 h:12 h

light: dark cycle. Fasting glucose and body weight were monitored weekly. Mice were

sacrificed by isoflurane inhalation followed by cardiac puncture.

LepR deficient mice (Leprdb) The 5-week old male leptin receptor deficient mice

(Homozygous for Leprdb) were randomly assigned to a control group treated with 10 μL

PBS/g body weight (BW) or AAC2 treatment (0.1 nmol/g BW). Six mice per group were

used for this study. Non-fasted mice were injected subcutaneously into the scapular region

every other day for 4weeks.

Leptin deficient mice (Lepob) The 5-week old male leptin deficient mice (Homozygous for

Lepob) were randomized and treated as Leprdb mice (n=5pergroup).

Wild type mice The aged male wild type mice (37–38 week old) were fed a high fat die

t(45% kcal from fat) to induce glucose tolerance. Mice were injected (i.p.) every other days

with 10μL PBS/gBW, (n=5), AAC2 (0.1nmol/gBW, n=5) for 4 weeks.

86

Monogenic model for phenotypes associated with T1D The 5 or 6-week old male C57BL/6-

Ins2Akita/J were injected intraperitoneally (i.p.) every other days with 10 μL PBS/g BW,

AAC2 (0.2 nmol/g BW), or hINS (1.7 nmol/g BW). Five mice per group were used for this

study.

87

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Chapter 3 Co-assembly of Two Oppositely Charged Peptides

3.1 Introduction

Self-assembly of short peptides is a well-studied field in supramolecular chemistry.

Assembly of peptides has been applied in drug delivery,1-4 nanomedicine,5-7, catalysis8-10

and many other subjects. Despite the simplicity of the building blocks, assemblies from

peptides may result in diverse nanostructures.11-13 Although peptide self-assembly has been

extensively studied and a great number of the research focus on single component

assemblies, multicomponent self-assembly still draw a lot of attention. Co-assembly of two

or more peptide building blocks could result in structures with higher structural complexity

and chemical diversity.14 Noncovalent interactions make these co-assembly systems much

easier to achieve compared to covalently bonded co-assemblies, which may require

complicated syntheses and purification steps. Furthermore, interplaying the ratio between

the components in co-assembly system could lead to changes in morphology, chemical and

mechanical properties. These unique features of multicomponent self-assembly are not

often found in single-component self-assembly. Hence, co-assembly of two or more

building blocks has attracted a lot of researchers and the study of this field is well-

developed over decades.

The motif of multicomponent self-assembly can generally be categorized as self-

sorted and co-assembled. Self-sorted assembly is the organization of distinctive structures

94

based on self-recognition of the building blocks in multicomponent system.15 It can be

narcissistic,16 meaning that the two building blocks form homo-structures separately and

there are no interactions between the homo-structures.15 Self-sorted assembly can also be

social when homo-structures formed by two or more building blocks associate together and

generate new hetero-structures.15-17 Co-assembled structures occur when two or more

different building blocks assemble into one nanostructure. There are several types of

molecular arrangement in co-assembled structure as described by Gazit, et al.:14

cooperative, random and disruptive co-assembly. In cooperative co-assembly, two building

blocks interact with each other and arrange in an alternating pattern.14 Random co-

assembly shows little to no order in the organization of different building blocks.14, 18 In

disruptive co-assembly, one building block can act as a stopper for the self-assembly of the

other building block.14

In order to promote co-assembly and social self-sorted assembly, many strategies

have been developed. Aromatic interaction is commonly used to achieve this goal. Nilsson

and co-workers utilized complementary π-π interactions between phenyl group on Fmoc-

Phe and fluorinated phenyl group on Fmoc-F5-Phe to obtain co-assembled nanofibrils.19

The aromatic side chains of the peptides had complementary quadrupole electronics, which

allowed Fmoc-Phe and Fmoc-F5-Phe to readily co-assemble into nanofibrils by face-to-

face quadrupole stacking interactions. In contrast, neither Fmoc-Phe and Fmoc-F5-Phe

were able to self-assemble individually. Additionally, Fmoc-Phe could also co-assemble

with mono-fluorinated Fmoc-Phe derivatives to yield nanofibrils. Collectively, the results

95

confirmed that the co-assembly was driven by π-π effects arising from the fluorination of

the benzyl side chain.19

Ulijn and co-workers explored the assembly and coassembly of serine surfactants

and tyrosine-leucine hydrogelators.20 Tyrosine-leucine and serine segments were

functionalized with pyrene and Fmoc to yield Py-YL, Py-S, Fmoc-YL and Fmoc-S

accordingly. All 4 peptide derivatives were able to self-assemble individually.

Hydrogelators Fmoc-YL and Py-YL self-assembled via aromatic and -sheet type H-

bonding interactions, while surfactants Fmoc-S and Py-S assembly was governed by

aromatic stacking and hydrophobic or hydrophilic interactions. Three different modes of

co-assembly were discovered when different peptides were combined (Figure 3.1).

Spectroscopic and microscopic experiments revealed that when individual building blocks

were sufficiently different in structure (Py-YL/Fmoc-S and Fmoc-YL/Py-S), orthogonal

assembly occurred. If the peptides were structurally similar (Py-YL/Fmoc-YL and Py-S/

Fmoc-S), cooperative co-assembly would be dominant. Moreover, disruptive co-assembly

would take place if the peptides had same aromatic moieties but different interactions on

the peptide segments. Overall, this work provided new insights in multicomponent

assembly design based on structural differences between individual components.20

96

Figure 3.1 Proposed supramolecular models for a) the gelators Pyr-YL and (Fmoc-YL);

b) the surfactants Fmoc-S and Pyr-S; c) orthogonal PyrYL/Fmoc-S and (Fmoc-YL/Pyr-

S); d) cooperative Pyr-YL/Fmoc-YL and Pyr-S/Fmoc-S; and e) disruptive Pyr-YL/Pyr-S

and (Fmoc-YL/FmocS). Copyright 2014 American Chemical Society.20

Enantiomeric interaction is also utilized in tuning multicomponent assembly.

Schneider and co-workers introduced two -hairpin peptides

VKVKVKVKVDPLPTKVKVKVKV-NH2 (MAX1) and

VKVKVKVKVLPDPTKVKVKVKV-NH2 (DMAX1), which possessed different chirality

on the proline moiety. CD spectra revealed that the hydrogel containing MAX1 and

DMAX1in 1:1 ration was racemic. In addition, co-assembled hydrogel had 4-fold higher

97

rigidity compare to enantiomerically pure hydrogels. The enhancement of mechanical

properties of co-assembled hydrogel resulted from hydrophobic interactions between

enantiomers which are not present in enantiomerically pure fibrils.21

External stimuli are also used in multicomponent assembly. Adams and co-workers

design two peptides present below (Figure 3.2 a).22 As the pH in the solution dropped from

10.5 to just below the apparent pKa of the terminal carboxylic acid, the peptides self-

assembled in self-sorted fashion. The author discovered that the pKa of the peptide was

determined by its hydrophobicity, indicating that the pH at which the peptide started to

self-assemble was predictable and controllable. The author also introduced slow hydrolysis

of glucono-d-lactone (GdL) to gluconic acid (Figure 3.2 b) in order to trigger self-sorted

assembly in situ.22 In a later publication, Adams and co-workers employed electrochemical

stimulation to trigger pH drop in the same two-component solution and induce self-sorted

assembly.23

Figure 3.2 a) Structures of gelators 1 (top) and 2 (bottom); b) Hydrolysis of GdL to

gluconic acid. Copyright 2013 Nature Publishing Group, a division of Macmillan

Publishers Limited.22

Electrostatic interactions between different building blocks in multicomponent

system can also result in change of self-assembly. In 2003, Stupp and co-workers

98

introduced a series of peptide amphiphiles with opposite charges at neutral pH.24 The

oppositely charged peptides were able to co-assembled to nanofibers via electrostatic

attraction and it was suggested that the co-assembled nanofibers could be potentially used

in biomedical fields.24 Lynn and co-workers synthesized two oppositely charged peptides

Ac-KLVFFAL-NH2 and Ac-(pY)LVFFAL-NH2 with different N-terminal residue lysine

and phosphotyrosine respectively.25 Both peptides formed nanotubes with charged inner

and outer surface when they self-assembled individually. Co-assembly of Ac-KLVFFAL-

NH2 and Ac-(pY)LVFFAL-NH2 yielded nanotubes comprising a bilayer of cross -sheets

with negative external and positive internal solvent exposed surfaces. Cross-seeding

peptide solutions with a preassembled peptide nanotube seed generated nanotubes with

different leaflet architecture. Furthermore, the asymmetry across the peptide bilayer and

along the lateral axis of the nanotube membranes could be controlled, which enabled

further construction of functional mesoscale assemblies.25

Cui and co-workers designed three peptides EFFFFE, KFFFFK, and EFFFFK to

elucidate -sheet stacking controlled by electrostatic interactions (Figure 3.3) .26 Individual

self-assembly of EFFFFE and KFFFFK showed multilayer twisted ribbon and fibrils

respectively. The twisting degree between the ribbon and the fibril resulted from different

scales of electrostatic repulsion on peptide termini. For both the homogeneous self-

assembly of EFFFFK and the heterogeneous assembly of EFFFFE/KFFFFK mixture,

twisting of -sheets were not present due to electrostatic attractions of the oppositely

charged groups on peptide termini. The lateral aromatic interaction between phenyl groups

offset the elastic penalty and led to multilayer stacking of -sheets. When EFFFFE or

99

KFFFFK co-assembled with EFFFFK, the charge was imbalanced. The flat nanobelt would

tend to twist or dissociate to grooved belts. Overall, the morphology of the co-assembled

structure could be controlled by manipulating the charge balance, which provided new

insight in precise morphological control on new materials.26

100

Figure 3.3 Proposed mechanism of the twisted ribbons, belts and fibrils formation by the

peptides EFFFFE, and EFFFFK, EFFFFE/KFFFFK mixture, and KFFFFK. Copyright

2015 American Chemical Society.26

In this study, we explored the self-assembly of two oppositely charged dipeptides

individually as well as when mixing in different ratios. We expected that electrostatic

attractions between the oppositely charged peptides would be able to alter the self-

assembly pattern when the peptides were combined. Nowadays, multicomponent self-

assembly has been widely used in material science and biomedical materials. Therefore,

101

the success of this study could provide a new insight of multicomponent self-assembly

study and potentially be applied in new material or medical fields.

3.2 Results and Discussion

Preliminary studies showed that electrostatic interactions can significantly

influence multicomponent assembly.25, 26 Hence, two oppositely charged peptides were

synthesized in this work. In chapter 2, a series of dipeptides named amino acid compound

(AAC) were synthesized and the self-assembly of the peptides were investigated.27 Inspired

by the design of AACs, N-(fluorenyl)-9-methoxycarbonyl (Fmoc) group was selected to

appended to the N-terminus of both dipeptides since Fmoc group can induce self-assembly

by aromatic stacking.20 Benzoic acid (BA) was selected to be appended to the second lysine

side chain of Fmoc-dislysine backbone since π-π interactions between BA moieties can

also enhance self-assembly. Positively charged dipeptide Fmoc-KK-BA was yield, which

was reported as AAC7 in chapter 2. 7-methoxycoumarin-3-carboxylic acid (MC) were

selected to append to lysine side chains of the peptide since π-π interactions between

aromatic moieties is a strong driving force of self-assembly and the inherent fluorescence

of MC enables monitoring self-assembly states by fluorescence spectroscopy or confocal

microscopy.28 Glutamic acid was utilized in order to obtain a negatively charged peptide

Fmoc-EK-MC. Since Fmoc-EK-MC has similar structure with AAC4 (Fmoc-EK-DAC)

reported in chapter 2, Fmoc-EK-MC will be addressed as AAC4’ in the following

discussion.

102

Figure 3.4 Structures of AAC7 and AAC4’.

AAC7 was dissolved in HPLC grade water at a concentration of 5 mM. The self-

assembly of AAC7 was the investigated by transmission electron microscope (TEM). After

24 h of aging at room temperature, twisted nanoribbons of 10 ± 1 nm and 20 ± 3 nm wide

were observed as majority. Meanwhile, wider coiled nanobelts of 40 ± 5 nm merging from

two 20 nm-wide nanoribbons were also found (Figure 3.5 a). After 5 days, TEM images

showed nanotubes with diameters ranging from 60 to 100 nm and length of a few

micrometers (Figure 3.5 b).

103

Figure 3.5 TEM images of AAC7 in HPLC grade water after a) 1 day and b) 1 week. The

sample were prepared at 5 mM and diluted to 1 mM for microscopic studies.

Dissolving AAC4’ in pure water at 5 mM resulted in opaque white solution. TEM

image of AAC4’ aged for 1 day only showed formation of very few nanofibers (Figure 3.6

a). However, as AAC4’ aged in HPLC grade water over a week, the solution became more

transparent and a large number of nanofibers with width of 10.5 ± 1.5 nm and length of

several micrometers were observed by TEM (Figure 3.6 b, c).

104

Figure 3.6TEM images of AAC4’ in HPLC grade water after a) 1 day and b) c) 1 week.

The sample were prepared at 5 mM and diluted to 1mM for microscopic studies.

The assembly behaviors of AAC7 and AAC4’ were further investigated by Fourier

transform infrared (FT-IR) spectroscopy. The samples were self-assembled in D2O for 1

week, lyophilized for 2 days to remove solvent and redissolved in D2O for FT-IR

measurement. After deconvolution, wavenumbers of 1628 was observed from the spectrum

of AAC7 (Figure 3.7 a), which are characteristic of β-sheet secondary structures.29 A minor

peak at 1648 cm-1 on the spectrum indicated that α-helix was also present in the assembly.29

Calculation of secondary structures indicated that self-assembly of AAC7 comprised

87.3% -sheet and 12.7% α-helix (Figure 3.7 c). On the other hand, FT-IR spectrum of

AAC4’ (Figure 3.7 b) displayed a strong peak at 1635 cm-1 and a weaker peak at 1653 cm-

1, which indicated both β-sheet and α-helix structures correspondingly.29 Calculation

showed that AAC4’ consisted of 74.8% β-sheet and 25.2% α-helix (Figure 3.7 c).

105

Figure 3.7 Deconvoluted FT-IR spectra of a) AAC7 and b) AAC4’. The samples were

prepared in D2O (5 mM) and set for 1 week. Then the samples were lyophilized for 2

days to remove solvent and redissolved in D2O (5 mM) for measurement. c) Calculated

percentage of secondary structures of AAC7 and AAC4’.

TEM studies revealed that neither AAC7 nor AAC4’ formed any self-assembled

structures in trifluoroethanol (TFE) at 5mM. Thus, it was considered that AAC7 and

AAC4’ were in monomeric state in TFE and UV-Vis and CD spectra of both peptides in

TFE (5mM) and HPLC grade water (5mM) were then compared. UV-Vis spectroscopy

showed that AAC7 in TFE displayed abosoption maxima at 262 and 297 nm (Figure 3.8

c), which corresponded to π-π* and n-π* transition of Fmoc and benzyl amidyl groups on

the peptide.30 Changing the solvent from TFE to water resulted in reduced intensity and

red-shifted peaks from 262 and 297 nm to 264 and 300 nm respectively (Figure 3.8 c),

indicating that J-type aggregation was present in AAC7 assembly. CD spectrum of AAC7

106

in water exhibited excitonic couplet with zero crossing at 267 nm (Figure 3.8 e). On the

contrary, a flat line was observed in TFE, which further confirmed that AAC7 was in

monomeric state in TFE (Figure 3.8 a). Provided that excitonic couplet was not observed

in TFE, the excitonic couplet of AAC7 in water should originate from distinct orientations

between the Fmoc groups. The electric transition moment of the excitation band at 264 nm

for Fmoc group runs approximately along the long axis of the functional group.30 The

positive couplet indicated that Fmoc group on AAC7 stacked in P-type helical fashion. .

UV-Vis spectrum of AAC4’ in TFE showed absorption maxima at 258, 300 nm

(Figure 3.8 d), which corresponded to π-π* and n-π* transition of Fmoc group.30 Another

peak at 350 nm was also observed (Figure 3.8 d), which was related to MC moiety on the

peptide. As the solvent switched to water, the intensity of absorbance reduced significantly.

The peaks at 258, 300 and 350 nm red-shifted to 260, 304 and 352 nm respectively (Figure

3.8d). Also, the peak at 350 nm displayed shoulder peak at 370 nm (Figure 3.8 d). Overall,

the red-shifted absorption indicated J-type aggregation of Fmoc and MC group in AAC4’

assembly. Emergence of shoulder peak at 350 nm also confirmed that coupling between

MC groups were present in the assembly.31 CD spectra of AAC4’ in water (5mM) and in

TFE (5mM) were also investigated. AAC4’ in TFE displayed a flat line (Figure 3.8 b). The

CD spectrum of AAC4’ in water showed a positive Cotton effect in the range of 260-390

nm, which originated from π-π* transition of MC moieties on the peptide (Figure 3.10 f).

A negative excitonic coupling with zero crossing at 254 nm and absorption maximum at

260 nm was also observed (Figure 3.10 f), which arised from π-π* transition of electric

107

transition moment that runs along the long axis of Fmoc group. The negative couplet

indicated that Fmoc groups stacked in a M-type helical fashion in AAC4’ assembly.

108

Figure 3.8 CD spectra of a) AAC7 and b) AAC4’; UV-Vis spectra of c) AAC7 and d)

AAC4’. AAC7 and AAC4’ were self-assembled in HPLC grade water (5 mM) for a

week. Monomeric samples were prepared by dissolving AAC7 and AAC4’ in TFE (5

mM). The spectroscopic experiments were performed at 5 mM in a 0.1 mm quartz

cuvette. Co-plot of CD and UV-Vis spectra of e) AAC7 and f) AAC4’.

109

Further experiments revealed that the assemblies of AAC7 and AAC4’ were both

concentration dependent. TEM images of AAC7 self-assembled at 1 mM (Figure 3.9 a)

and 0.5 mM (Figure 3.9 b) for 5 days exhibited coexistence of nanotubes ranging from 60

to 100 nm, coiled nanobelts of 40 ± 5 nm and twisted nanoribbons of 20 ± 3 nm and 10 ±

1 nm, which were also observed at early stage of self-assembly at 5 mM (Figure 3.5 a).

When AAC4’ was dissolved in water at 1 mM, micrometer-long nanofibers with width of

13 ± 2 nm were still observed (Figure 3.9 c). However, spherical structures with diameters

ranging from 30-70 nm emerged at 0.5 mM (Figure 3.9 d).

110

Figure 3.9 TEM images of AAC7 self-assembled in HPLC grade H2O at a)1 mM and b)

0.5 mM; TEM images of AAC4’ self-assembled in HPLC grade H2O for 5 days at c) 1

mM and d) 0.5 mM.

UV-Vis spectra of AAC7 at 5 mM, 1 mM, 0.5 mM in water and 5mM in TFE were

shown in Figure 3.10 c. Comparing with AAC7 in TFE (5mM), AAC7 samples self-

assembled at 1 mM and 0.5 mM in water both displayed similar red-shifts of absorption

maxima like 5 mM sample in water. The peaks shifted from 262 and 297 nm to 264 and

111

300 nm respectively (Figure 3.10 c), indicating that J-type aggregation between the

aromatic moieties were also present in 1 mM and 0.5 mM AAC7 assemblies. CD spectra

of AAC7 at 5 mM, 1 mM, 0.5 mM in water and 5 mM in TFE were also compared. At 5

mM in water, strong excitonic couplet was observed in the range of 240-350 nm. Whereas

the intensity of the couplet decreased drastically in 1 mM and 0.5 mM assemblies (Figure

3.10 a), indicating that the interaction between Fmoc groups were declined in the

assemblies at 1mM and 0.5 mM. .

In the model developed by Aggeli, et al.,32-34 twisted -sheets could merge laterally

into various structures by stacking. The stacking number of -sheets depends on the

concentration of the peptide and the interactions among the side chains on the peptides.35

If the twisted -sheet grows laterally, it has to untwist itself to obtain close packing and

this process could cause shifting and intensity change of the -sheet absorbance peaks on

CD spectrum,36 which was shown in Figure 3.10 a. When the energy of lateral growth is

high enough to compensate the entropy loss of untwisting -sheets and electrostatic

repulsions, wider, coiled nanobelts and then nanotubes will occur. Based on CD

spectroscopy results, it is believed that the formation of nanotubes is driven by the π-π

interactions between Fmoc groups on AAC7 because the excitonic couplet at ~300 nm

occurs as concentration of AAC7 increases, indicating chiral arrangement between the

aromatic moieties and the energies of aromatic interaction are enough to overcome entropy

loss.

112

Figure 3.10 CD spectra of a) AAC7 and b) AAC4’ and UV-Vis spectra of c) AAC7 and

d) AAC4’ at 5 mM, 1 mM, 0.5 mM in HPLC grade water and 5 mM in TFE.

As AAC4’ was diluted from 5 mM to 1 mM, the intensity of excitonic couplets on

CD spectrum and the UV-Vis absorbance increased overall (Figure 3.10 b). Such

phenomenon could be due to the relatively low solubility of AAC4’ in water. At 5 mM,

small aggregates were observed in solution, which could lead to decreased absorbance on

CD spectrum. The CD spectrum of AAC4’ at 0.5 mM was unexpectedly different. The

excitonic couplets observed in higher concentrations intensively decreased at 0.5 mM. The

113

decline of excitonic couplet could be explained by the morphological change from

nanofibers to spheres with various sizes. At 0.5 mM, AAC4’ self-assembled in a different

pattern such that the chiral arrangement of MC moieties was not present anymore. The

disappearance of shoulder peak at 370 nm on UV-Vis spectrum also indicated stacking of

MC was depleted.

AAC4' AAC7

-40

-30

-20

-10

0

10

20

30

ze

ta p

ote

nti

als

(m

V)

Figure 3.11 Zeta potentials of AAC4’ and AAC7 at 1 mM in HPLC grade water.

Zeta potential measurements revealed that AAC7 had zeta potential of 22 mV and

AAC4’ had zeta potential of -35 mV at 1mM in HPLC grade water (Figure 3.11). Due to

the opposite charges on the self-assemblies of AAC7 and AAC4’, electrostatic interactions

could lead to combination of the two components and potentially morphological changes.

Hence, pre-assemblies of AAC7 and AAC4’ at 5 mM in HPLC grade water were combined

in a 1:1 ratio by volume and the mixed sample was investigated first.

114

Figure 3.12 a) Co-plot of CD and UV-Vis spectra and b) TEM image of AAC7:AAC4’

(1:1) mixture. AAC7 and AAC4’ were pre-assembled in HPLC grade water at 5 mM for

1 week and then combined in 1:1 ratio by volume. The mixture was set at room

temperature for 3 days and diluted to 1 mM for spectroscopic and microscopic studies.

TEM image of the AAC7:AAC4’ (1:1) mixture showed that both nanotubes of

AAC7 and nanofibers of AAC4’ were present (Figure 3.12 b). Nanotubes with distinct

morphology compare to AAC7 were observed (Figure 3.12 b). The new nanotube assembly

could originate from lateral association of AAC7 nanoribbons that were unwrapped from

nanotubes, and AAC4’ nanofibers via electrostatic attraction. Such lateral self-assembly

mechanism was reported by Frisch et al.37.UV-Vis spectrum (Figure 3.12 a) exhibited that

the absorbance peaks at 264 and 300 nm were identical to AAC7 and AAC4’ spectra

measured above (Figure 3.10 c, d). The absorbance of MC at 350 nm was lower and the

peak shape was even broader compared to AAC4’ at 5 mM (Figure 3.10 c), which resulted

from stronger interactions between the electric dipoles along the long axis on MC

moieties.31 The CD spectrum was significantly different from preliminary results. The

115

overall intensity of CD spectrum of the AAC7:AAC4’ (1:1) mixture at 5 mM decreased

drastically and it could result from the relatively low solubility of the AAC7:AAC4’ (1:1)

mixture since positively charged AAC7 could form an ion pair with negative charged

AAC4’ thus generating aggregates in solution. However, a weak positive excitonic couplet

in 320-375 nm with zero crossing at 330 nm was still observed, which was related to chiral

packing of MCs on the peptides. A positive peak at 300 nm and a negative at 265 nm were

also observed and they could be corresponding to aromatic rings such as Fmoc and

benzylamidyl groups on AAC7 and AAC4’.

116

Figure 3.13 a) CD spectra and b) UV-vis spectra of pre-assembled AAC7:AAC4’ (2:1)

and (5:1) mixtures. TEM image of c) pre-assembled AAC7:AAC4’ (2:1) mixture and d)

pre-assembled AAC7:AAC4’ (5:1) mixture. AAC7 and AAC4’ were self-assembled in

HPLC grade water (5 mM) separately for 1 week, then the samples were made by

combining AAC7 and AAC4’ in different ratios by volume.

At 1:1 ratio, the large amount of AAC4’ nanofibers made finding the nanotubes

difficult. Hence, we decide to lower the ratio of AAC4’ in the following studies.

AAC7:AAC4’ pre-assembled mixtures at 2:1 and 5:1 were investigated. TEM images of

117

both 2:1 and 5:1 mixtures showed free nanofibers and nanotubes laminated with nanofibers

(Figure 3.13 c, d). UV-Vis spectra of 2:1 and 5:1 both exhibited peaks at 264 and 300 nm.

Broaden peak with low intensity at 350 nm were observed in both samples. The absorbance

at 200, 264 and 300 nm of the 5:1 sample was higher than the 2:1 sample. On the contrary,

the absorbance at 350 nm was lower in 5:1 sample compared to the 2:1 sample. The

variation of UV-Vis absorbance intensities at distinct wavelengths resulted from different

percentages of AAC7 and AAC4’ in the samples.

The CD spectrum of 2:1 sample showed strong negative peaks at 215 and 270 nm

and weak positive peak at 307 nm and broad positive peak in 340-380 nm. In the 5:1

sample, negative peaks at 214 and 267 nm and positive peaks at 307 nm and in 340-380

nm were observed. The CD signals of 2:1 and 5:1 samples were stronger compare to 1:1

sample, which could due to less aggregation in the mixtures since AAC7 was in excess and

less ion pairs were present in the samples. The negative peaks at ~215 nm and positive

peaks at ~195 nm, which corresponded to π-π* and n-π* transition on amide respectively,

indicated that -sheets structures were present.36 Cotton effects shown in 260-310 nm

demonstrated chiral arrangement of Fmoc groups. The excitonic couplets corresponding to

MC in both samples were strongly diminished compare to AAC4’. Experimental CD

spectra of pre-assembled AAC7:AAC4’ mixtures were also compared with theoretical

spectra calculated from simple ratiometric combination of data from the parent peptides

(Figure 3.14). If there was no interaction between pre-assembled AAC7 and AAC4’

structures, the expected CD spectra should be identical to the sum of the spectra of two

parent peptides, which is shown in dash line in figure 3.14 a. However, the spectra obtained

118

from the mixtures were dramatically different in magnitude and key signature peaks.38, 39

All in all, the drastic difference between experimental CD spectra and theoretical CD

spectra suggested that electrostatic interaction between assembled AAC7 and AAC4’ were

present.

200 300 400 500 600

-200000

-150000

-100000

-50000

0

50000

100000

Mo

lar

Ellip

ticit

y [q]

Wavelength (nm)

1 to 1

2 to 1

5 to 1

1 to 1 (cal.)

2 to 1 (cal.)

5 to 1 (cal.)

Figure 3.14 Co-plot of theoretical (dash line) and experimental (solid line) CD spectra of

AAC7:AAC4’ at 1:1, 2:1 and 5:1 ratio. Theoretical CD spectra were obtained from

simple ratiomatic combination of data from AAC7 and AAC4’.

FT-IR spectra of 1:1, 2:1 and 5:1 pre-assembled mixtures of AAC7 and AAC4’

were taken and compared. Experimental results showed that all pre-assembled mixtures of

AAC7 and AAC4’ had -sheet and α-helix in the assemblies (Figure 3.15 a-c), which were

119

also observed in spectra of AAC7 and AAC4’ (Figure 3.15 d). Interestingly, the percentage

of -sheet decreased as the molar ratio of AAC7:AAC4’ increased (Figure 3.15 e),

indicating that the pre-assembled structures of AAC7 and AAC4’ remained even after

combining.

120

Figure 3.15 Deconvoluted FT-IR spectra of pre-assembled AAC7:AAC4’ mixtures at

ratio of a) 1:1, b) 2:1 and c) 5:1. d) Co-plot of FT-IR spectra of pre-assembled

AAC7:AAC4’ mixtures, AAC7 and AAC4’. AAC7 and AAC4’ were prepared in D2O

(5mM) and set for 1 week. Then the samples were combined in different ratios, set at

room temperature for 3 days and then lyophilized for 2 days to remove solvent. The dried

samples were redissolved in D2O for measurement. e) Calculated percentage of

secondary structures in pre-assembled AAC7:AAC4’ mixtures.

121

To further investigate whether deviation between experimental and theoretical CD

spectra was related to the interaction between pre-assembled AAC7 and AAC4’,

fluorescence spectroscopy was used. Since the excitonic couplet generated from MC

stacking changed drastically in experimental CD spectra that the intensity of the peaks were

significantly lower compare to calculated CD spectra, the fluorescence activity of

AAC7:AAC4’ mixtures were investigated and compared with AAC4’. Fluorescence

measurements showed that AAC4’ in water had λmax of emission at 411 nm (Figure 3.16).

However, λmax of emission for the 1:1 mixture red-shifted to 420 nm (Figure 3.16). For 2:1

and 5:1 mixtures, λmax of emission both blue-shifted to 407 nm (Figure 3.16). The shifting

of λmax on the emission spectra of AAC7:AAC4’ mixtures indicated that the supramolecular

interaction between MC moieties on the peptides were different from AAC4’ assembly.40

If pre-assembled AAC7 and AAC4’ were self-sorted in the mixture, the emission spectra

should be identical to fluorescence spectrum of AAC4’. Whereas the fluorescence spectra

were different for pre-assembled AAC7/AAC4’ mixtures, indicating that there was

interactions between AAC7 and AAC4’ and that affected the electronic levels involved in

MC emission.

122

350 400 450 500 550 600

0.0

0.2

0.4

0.6

0.8

1.0

No

rma

lized

In

ten

sit

y

Wavelength (nm)

1 to 1

2 to 1

5 to 1

AAC4' only

Figure 3.16 Normalized fluorescence spectra of AAC4’ and pre-assembled

AAC7:AAC4’ mixtures in 1:1, 2:1 and 5:1 ratios. All samples were diluted from 5 mM to

1 mM. Fluorescence spectra were measured using 3 mM quartz cuvette. The samples

were excited at 350 nm.

AAC7 and AAC4’ were also combined as monomers at different ratios and then

co-assembled in water in order to compare with pre-assembled mixture of AAC7 and

AAC4’. To ensure the peptides were mixed in molecular level and to remove any pre-

assembled structure, AAC7 and AAC4’ were first dissolved in TFE separately and then

mixed in desired molar ratio and followed by lyophilization. Afterwards, the lyophilized

sample was dissolved in water with 10% TFE at 5 mM due to the low solubility of the

sample. TEM was used to investigate the assembly of the co-assembled samples.

123

Surprisingly, nanofibers with width of 13 ± 2 nm and length of micrometers were observed

in co-assembled samples in ratios of 1:1, 2:1 and 5:1(Figure 3.17 a-c).

Figure 3.17 TEM images of co-assembled AAC7:AAC4’ at ratios of a) 1:1; b) 2:1; c) 5:1.

The samples were prepared at 5 mM and diluted to 1 mM for microscopic studies.

UV-Vis spectra of 1:1, 2:1 and 5:1 mixtures (Figure 3.18 b) all exhibited absorption

peaks at 265 and 300 nm, which corresponded to π-π* and n-π* transition of Fmoc and

benzyl amidyl groups. The peak intensity increased as the molar ratio of AAC7 was higher,

indicating that absorbance change in these wavelengths were related to concentration of

AAC7 in the mixture. A weak peak was observed in 310-380 nm, which was related to MC

group on AAC4’. From the inset of figure 3.17 b, a broad peak with λ max at 350 nm and

shoulder peak at 370 nm were observed in the 1:1 ratio of AAC7 and AAC4’, indicating

chiral interaction between MC groups. The absorbance at 350 nm increased and the

shoulder peak intensity was lower for the 2:1 sample. The drop of shoulder peak intensity

showed that intermolecular interactions between MC groups were weaker due to lower

molar ratio of AAC4’ in 2:1 sample. Absorbance in 310-380 nm was even lower in 5:1

124

sample, but the shoulder peak did not change, indicating the interaction between MC in 5:1

ratio was similar to that in the 2:1 sample.

CD spectroscopy revealed distinctive spectra of co-assembled AAC7:AAC4’

samples (Figure 3.18 a) compare with pre-assembled AAC7:AAC4’ mixture. The positive

Cotton effect was much weaker in the spectra of all co-assembled samples. Signature

negative peaks at ~215 and ~265 nm were not seen in all CD spectra, indicating that

supramolecular motif observed in AAC7 were not present. The observation from these CD

spectra was in agreement with the TEM results because wide nanotube structures were not

seen (Figure 3.17 a-c). Positive excitonic couplets were observed in the range of 310-390

nm, which indicated that P-type helical stacking between MC moieties was present.

Figure 3.18 a) CD spectra and b) UV-Vis spectra of co-assembled AAC7:AAC4 at 1:1,

2:1 and 5:1 ratios. The samples were prepared at 5 mM in HPLC grade water with 10%

TFE and diluted to 1 mM for spectroscopic and microscopic studies.

FT-IR spectroscopy was utilized to investigate the secondary structures of co-

assembled samples of AAC7 and AAC4’. In the spectrum of 1:1 sample, only -sheet with

125

wavenumber at 1616 and 1636 cm-1 was shown (Figure 3.19 a). For 2:1 sample, -sheet

structure was also observed with peaks at 1622, 1628 and 1634 cm-1. Whereas a large peak

at 1644 cm-1 emerged on the spectrum, indicating that random coil was present in the

assembly (Figure 3.19 b). For 5:1 sample, not only -sheet peaks at 1622 and 1633 cm-1

and random coil peak at 1644 cm-1 were observed, a peak at 1650 cm-1 revealed that α-

helix was also present in 5:1 co-assembly of AAC7 and AAC4’. The distinct FT-IR spectra

of AAC7:AAC4’ co-assembly suggested that the supramolecular arrangement of the

peptides was different from both AAC7 and AAC4’ (Figure 3.19 d).

126

Figure 3.19 Deconvoluted FT-IR spectra of co-assembled AAC7:AAC4’ mixtures at ratio

of a) 1:1, b) 2:1 and c) 5:1. AAC7 and AAC4’ were first dissolved in TFE (5 mM),

combined in different ratios and lyophilized. The dried mixtures were dissolved in D2O

with 10% TFE (5mM) and set for 1 week and then lyophilized for 2 days to remove

solvent. The samples were redissolved in D2O for measurement d) Co-plot of FT-IR

spectra of co-assembled AAC7:AAC4’ mixtures, AAC7 and AAC4’.

Fluorescence measurement was performed on co-assembled samples of AAC7 and

AAC4’ (Figure 3.20). Fluorescence spectra of 1:1, 2:1 and 5:1 samples exhibited λmax of

127

emission at 411 nm, which was identical to AAC4’. The same λmax of emission of co-

assembled samples and AAC4’ indicated that the supramolecular interactions between MC

moieties in these co-assembled samples were similar.

350 400 450 500 550 600

0.0

0.2

0.4

0.6

0.8

1.0

No

rma

lized

In

ten

sit

y

Wavelength (nm)

1 to 1

2 to 1

5 to 1

AAC4' only

Figure 3.20 Normalized fluorescence spectra of AAC4’ and co-assembly of

AAC7:AAC4’ in 1:1, 2:1 and 5:1 ratios. All samples were diluted from 5 mM to 1 mM.

Fluorescence spectra were measured using 3 mM quartz cuvette. The samples were

excited at 350 nm.

The preliminary results showed that when AAC7 and AAC4’ were mixed in

monomeric form, the self-assembly would be very different from the mixture of pre-

assembled peptides. The absence of signature -sheet peaks on CD spectra indicated that

the motif of AAC7:AAC4’ co-assembly was not similar to AAC7 itself. The positive cotton

effect in 310-390 nm on the CD spectra exhibited that the supramolecular interaction

128

between MC groups in the co-assembly of AAC7 and AAC4’ resembled the stacking motif

in AAC4’. Identical λmax of fluorescence emission for MC also agreed with observation

from CD spectroscopy. Hence, it is possible that the co-assembled nanofibers comprise

AAC4’ segments (Figure 3.21), which has same assembly pattern to AAC4’ nanofibers

and AAC7 segments that have completely different supramolecular arrangement compare

to AAC7 nanotubes.

Figure 3.21 Proposed AAC7:AAC4’ self-assembly. a) AAC7 and AAC4’ are pre-

assembled in water to yield distinct nanostructures. Pre-assembled AAC7 and AAC4’

form the complex showed on the right via electrostatic attraction. b) AAC7 and AAC4’

are combined in monomeric form. The co-assembled nanofibers comprise segments of

AAC4’ and AAC7.

129

Conclusion

In summary, positively charged peptide AAC7 and negatively charged peptide

AAC4’ were able to self-assemble into nanotubes and nanofibers respectively.

Spectroscopic and microscopic studies revealed that the morphology of AAC7 and AAC4’

assemblies were concentration dependent. As pre-assembled AAC7 and AAC4’ were

combined at ratio of 1:1, 2:1 and 5:1, nanotubes with distinct morphology compare to

AAC7 were observed. On the contrary, when AAC7 and AAC4’ were combined in

monomeric form at 1:1, 2:1 and 5:1 ratio, nanofibers were observed in all samples. The

morphology of co-assembled peptides was distinctive compare to the mixture of pre-

assembled peptides. Spectroscopic and microscopic results further proved that co-assembly

motif of AAC7 and AAC4’ were different from pre-assembled mixture of AAC7 and

AAC4’. Overall, this study provided a new insight on multicomponent self-assembly and

further exploration on the motifs of self-assemblies in this study could be helpful in

designing functional multicomponent self-assembled materials.

3.3 Experimental Section

Synthesis of MC

2-Hydroxy-4-methoxybenzaldehyde (3.04 g, 20 mmol), diethylmalonate (6.40 g, 40 mmol)

and piperidine (2 mL) were combined in absolute ethanol (60 mL) and stirred for 6 h at

reflux. Then 10% NaOH (60mL) aqueous solution was added to the mixture and the

solution was heated at reflux for 15 minutes. The reaction mixture was cooled down to

130

room temperature and the pH of the mixture was adjusted to 2 with concentrated

hydrochloric acid to obtain an light yellow precipitate. The crude product was filtered,

washed with cold water and recrystallized into white crystal in absolute ethanol (2.77g,

63%).

Scheme 3.1 Synthesis of MC

General Peptide Preparation

The peptide is synthesized using a solid phase peptide coupling protocol on Rink amide

resin (0.8 g/mmol). All amino acids were coupled using Fmoc-protected amino acids, DIC

and HOBt, which were combined in DMF and reacted for 2 h. The Fmoc group was

removed using 20% piperidine in DMF and the Mtt group was deprotected using

TFA/TES/DCM (2:1:97). Boc and tBu groups were removed using TFA/TES/H2O (94:5:1)

at the final cleaving step. MC and benzoic acid were coupled on the deprotected lysine side

chain using HOBt, HBTU and DIPEA to yield AAC4’ and AAC7 respectively. The final

peptides were cleaved with TFA/TES/H2O (94:5:1). After cleavage from the solid support,

all AAC peptides were purified by high performance liquid chromatography. AAC

structures were validated using 1HNMR and13CNMR and mass spectroscopy.

131

Scheme 3.2 Synthesis of AAC7

AAC7 1H NMR (700 MHz, DMSO-d6) δ 8.42 (1H, t, J=5.9 Hz), 7.90 (2H, d, J=7.1Hz),


Hz), 7.50 (1H, d, J=7.3 Hz), 7.40-7.46 (5H, m), 7.38 (1H, s), 7.33 (2H, t, J=7.4Hz), 7.03

(1H, s), 4.28 (2H, m), 4.22 (2H, m), 4.00 (1H, m), 3.23 (2H, m), 2.76 (2H, m), 1.62-1.72

(2H, m), 1.47-1.59 (7H, m), 1.27-1.37 (5H,m); 13C NMR (176MHz, DMSO-d6) δ 173.98,

172.04, 166.55, 156.45, 144.38, 144.20, 141.20, 135.15, 131.46, 128.88, 128.12, 127.57,

125.76, 125.72, 120.62, 120.60, 120.51, 66.08, 54.89, 52.63, 47.14, 40.50, 39.24, 32.43,

31.75, 29.37, 27.11, 23.24, 22.79; ESI-MS for C34H41N5O5 [M+H]+ calculated 600.3180;

found 600.3189.

132

Scheme 3.3 Synthesis of AAC4’

AAC4’ 1H NMR (700 MHz, DMSO-d6) δ 8.94 (1H, s), 8.77 (1H, t, J=5.6 Hz), 8.03 (2H,

d, J=8.7 Hz), 8.02 (2H, d, J=6.7 Hz), 7.98 (1H, d, J=8.1 Hz), 7.87 (1H, d, J=7.5 Hz), 7.85

(1H, d, J=7.5 Hz), 7.70 (1H, d, J=8.1 Hz), 7.55 (2H, t, J=7.38 Hz), 7.50 (1H, s), 7.46 (2H,

t, J=7.4 Hz), 7.24 (1H, d, J=2.2 Hz), 7.18 (2H, dd, J= 8.7, 2.4 Hz), 7.16 (1H, s), 4.40 (2H,

d, J=7.2 Hz), 4.34 (2H, m), 4.18 (1H, m), 4.03 (3H, s), 3.42 (2H, m), 2.41 (2H, t, J=7.92),

2.05 (1H, m), 1.90 (1H, m), 1.82 (1H, m), 1.61-1.73 (3H, m), 1.46 (2H, m); 13C NMR

(176MHz, DMSO-d6) δ 171.66, 164.82, 161.76, 161.35, 156.59, 156.39, 148.16, 144.37,

144.19, 141.16, 131.97, 128.09, 127.55, 125.79, 125.76, 120.55, 115.39, 114.09, 112.61,

100.73, 66.16, 56.71, 54.45, 52.58, 47.10, 39.41, 32.22, 30.71, 29.20, 27.75, 23.15; ESI-

MS for C37H38N4O10 [M+23]+ calculated 721.2480; found 721.2487.

133

Circular Dichroism (CD) Spectroscopy Measurement.

CD spectra were recorded on a Jasco CD J-815 spectrometer under nitrogen atmosphere.

Experiments were performed in a quartz cell with a 1 mm path length at 1mM and 0.5mM

and with a 0.1mm path length at 5mM over the range of 190-600 nm. Samples were

prepared as 5mM solution in H2O after 1-week incubation at room temperature, and

subsequently diluted before the measurement.

Fourier Transform Infrared (FT-IR) Spectroscopy Measurement

FT-IR spectra were collected on a Shimadzu FTIR spectrometer at ambient temperature.

Spectra were recorded between 1700 and 1600 cm-1 at a resolution of 4 cm-1, and a total of

128 scans were averaged. Samples for FT-IR were first dissolved in D2O (5mM) and

freeze-dried to remove water. Spectra were analyzed in a transmission cell having CaF2

windows and a 0.025 μm path length. After subtracting the solvent spectrum from the

sample spectrum, the amide I band (1600-1700 cm-1) of each spectrum was analyzed using

peak fit with Gaussian method on Origin. The contribution of each peak to the amide I

band were quantified by the integrated areas of respective peaks.

Transmission Electron Microscopy Measurement

AAC4’ and AAC7 were dissolved in Millipore water to form 5mM solution and left to self-

assemble for 1 week. Afterwards, the sample was diluted to1mM and 30 μL diluted samples

were loaded on the formvar/carbon-covered copper grid and stained with uranyl acetate (2

wt% in distilled water) for 50 s and the grids were dried with filter paper. Then

nanostructures of the AAC4’ and AAC7 were observed by TEM.

134

Zeta Potential Measurement

Zeta potential measurements were performed on AAC7 and AAC4’. The peptides were

prepared as 5mM solution in H2O and aged for 1 week before diluted to 1mM for zeta

potential measurement on Malvern Zetasizer Nano ZS.

135

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Appendix A: NMR spectrum

Self-Assembly of Short Peptide Derivatives

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