IN SILICO SEARCH OF SOME CHEAP ANTIBIOTICS-PART-1

www.wjpps.com Vol 3, Issue 5, 2014.

1314

Srivastava et al. World Journal of Pharmacy and Pharmaceutical Sciences

IN SILICO SEARCH OF SOME CHEAP ANTIBIOTICS-PART-1

*K.K.Srivastava1, Shubha Srivastava2 , Md. Tanweer Alam, Rituraj

1Department of Chemistry, Vinoba Bhave University, Hazaribagh, India. 2Department of Chemistry, KBW College, Hazaribagh , India.

ABSTRACT

In search of some cheap antibiotics, molecular docking studies with

proteins 1BSK and 1S17 were carried out using certain succinic acid

derivatives. Some of the derivatives of succinic acid were found to

have binding energy and docking pattern very close to the originally

docked molecule in 1BSK and 1S17. The docking result of succinic

acid derivatives with the two proteins shows the more effectiveness

with some well-known antibiotic such as norfloxacine, Ciprofloxacin

and ofloxacin. The quick prop results reveal that these molecules are

non-toxic. Some of the succinic acid derivatives shows higher docking

score compared to originally docked ligand in 1S17 protein.

Keyword: Molecular docking, 1BSK, 1S17, succinic derivatives, antibiotic ,quick prop,

druggability.

INTRODUCTION

Peptide deformylase (PDF), an essential bacterial metalloenzyme, is responsible for the

removal of the N–terminal formyl group from methionine residues following protein

synthesis[1] Because PDF is essential in a variety of pathogenic bacteria but is not required

for cytoplasmic protein synthesis in eukaryotes, it is an attractive target for developing novel

antibiotics [2,3] and PDF inhibitors are one of the most promising classes of antibacterial

agents discovered to date. Several classes of PDF inhibitors have been reported [4-7] and

among them some compounds have a pseudopeptidic scaffold [8,9] and others are –sulfonyl

and β –sulfinylhydroxamic acid derivatives[10]. PDF Peptide deformylase (PDF) is essential

in a variety of pathogenic . bacteria but it is not required for cytoplasmic protein synthesis in

eukaryotes. Most PDF inhibitors have the general structural characteristics of a 'ion binding

WWOORRLLDD JJOOUURRNNAALL OOFF PPHHAARRMMAACCYY AANNDD PPHHAARRMMAACCEEUUTTIICCAALL SSCCIIEENNCCEESS

VVoolluummee 33,, IIssssuuee 55,, 11331144--11333333.. RReesseeaarrcchh AArrttiiccllee IISSSSNN 2278 – 4357

Article Received on 08 March 2014, Revised on 01 April 2014,

Accepted on 24 April 2014

*Correspondence for Author

K.K.Srivastava

Department of Chemistry,

Vinoba Bhave University,

Hazaribagh, India.


1315


domain peptide analogues'. However, there is still an urgent need for the development of new

and different structure of the non-peptide PDF inhibitor.

Inquest of cheap and effective antibiotics, in this paper we report the results of molecular

docking studies of some succinic acid derivatives on proteins designated by PDB Id’s 1BSK

and 1S17. The molecular docking studies have also been carried out with commonly used

antibiotics such as norfloxacin, ofloxacin, ciprofloxacin and the ligands docked with the

target proteins with a view to compared the docking scores with the drug candidate

molecules. The druggability of these compounds having good docking scores are also being

reported.

MATERIAL AND METHODS The molecular docking studies were carried out on glide 5.0 platform of Schrodinger 2012

software. The druggability was also studied with the help of quick prop program of the same

software. The peptide deformylase inhibitors, 1BSK and 1S17 were downloaded from the

site RCSB.org. The general description of target proteins have been described below:-

a) 1BSK: This target protein was isolated from the pathogenic micro-organism Escherichia

coli The crystal structure of 1BSK having structural weight19832.16 was determined by

Hao, B., Gong et.al[ 11 ] using X-ray diffraction at a resolution of 3.0 Å. The PDB entry

contains the structure of protein (peptide deformylase). This molecule has the UniProt

identifier P0A6K3 (DEF_E.COLI). The sample contained 168 residues which is 99% of the

natural sequence. Out of 168 residues 166 were observed and are deposited in the PDB. It

also contains one or more heterogenic compounds (e.g., ligands, co-factors, ions, modified

amino acids, etc.).The molecule is most likely monomeric.

b) 1S17: This target protein was isolated from the pathogenic micro- Pseudomonas

aeruginosa The structure of 1S17 having structural weight 20867.0 was published by

Molteni, V.etal. This crystal structure was determined using X-ray diffraction at a resolution

of 1.95 Å . This PDB entry contains multiple copies of the structure of Peptide deformylase.

It also contains one or more heterogenic compounds (e.g., ligands, co-factors, ions, modified

amino acids, etc.);. The molecule has more than one probable quaternary state observed.. It

has two chains (A,B).


1316


The general comparison of the two target proteins appears in Table1 Table. 1

1BSK 1S17 Chain A PROTEIN(PEPTIDE

DEFORMYLASE) A Peptide deformylase

PROTEIN(PEPTIDE DEFORMYLASE)

B Peptide deformylase

Name UniProt A 0917A8(1-168)

(DEF PSEAE) POA6K3 (2-169)

DEF ECOLI B 0917A8(1-168)

(DEF PSEAE) Name of source organism

Escherichia coli K12 A Pseudomonas aeruginosa PA01

Escherichia coli K12 B Pseudomonas aeruginosa PA01 % of UniProt sequence present in the sample

97% A 99%

B 99% Residue in the sample molecules

168 A 180

B 180 % of residue observed

98% A 92%

B 92% UniProt accession POA6K3 (2-169) Name PROTEIN (PEPTIDE

DEFORMYLASE)

*Organism Escherichia coli Pseudomonas aeruginosa Chain A (POA6K3) A,B

(Q917A8) Structural classification (SCOP)

Peptide deformylase Peptide deformylase

Structural classification (CATH)

Peptide deformylase Peptide deformylase

Sequence family (Pfam)

PF01327 (Polypeptide deformylase)

PF01327 (Polypeptide deformylase)

Molecular function (GO)

Peptide deformylase activity, Iron ion binding, metal ion binding, hydrolase activity, protein binding, zinc ion binding, ferrous ion binding

Hydrolase activity, formylmethionine deformylase activity, peptide deformylase activity, metal ion binding, iron ion binding


1317


Biological process(GO)

N-terminal protein amino acid modification, co-translational protein modification translation.

Translation cellular protein metabolic process, cellular protein modification process

InterPro annotation Formylmethionine deformylase, Peptide deformylase

Chain A,B Formylmethionine deformylase, Peptide deformylase

*Diseases caused by the parent organism

diarrhea, anemia, kidney failure, urinary tract infections

Endocarditis, Respiratory infections, Bacteremia and septicemia, Central nervous system infections

Computational studies

The molecular docking studies were done on the 1BSK and 1S17 by downloading it on the

glide software of Schrodinger 2012. The validation of the docking protocol was carried out

by removing the co-crystallized originally docked molecule from the binding site and re-

docking it to the 1BSK and 1S17 separately. We found very good agreement between the

localization of the inhibitor 1BSK and 1S17 upon docking and from crystal structure.

Protein preparation : The downloaded protein had some problems , so preparation of

protein was needed before docking . This was done in the protein preparation wizard from the

workflow menu following the method prescribed by Schrodinger 2012 user manual.

Ligand Preparation : The initial structures of all the ligands were drawn with Chem-Draw

ultra 8.0 and the structures were optimized on Chem3D ultra 8.0. The saved mol files of these

structures were imported and prepared by the method prescribed in the manual of the Maestro

9.3 of Schrodinger 2012 version software and these prepared molecules were finally docked

with the two desired target proteins.

Receptor Grid Generation

Receptor grid of the prepared 1BSK and 1S17 protein were generated before docking

following the prescribed method

The docking of the ligands to the generated receptor grid was carried out without imposing

any constraint. The docking pose, binding energy and details of other interactions including

the ligand interaction diagram, were visualized on the monitor. The drug properties were

determined on the quick prop protocol of the same software.


1318


RESULTS AND DISCUSSION

The results of molecular docking LD50,LC50 and EC50 of some antibiotics in clinical use,

succinic acid derivatives(drug candidates) and ligand originally docked with the target

proteins such as Ofloxacin (1a), 3-(methoxycarbonyl)-4,4-diphenylbut-3-enoic acid(1b),

1BSKligand(1c), 2-(diphenylmethylene)succinic acid(1d) (2E,3Z)-3-(methoxycarbonyl)-2-

((furan-2-yl)methylene)-4-phenylbut-3-enoic acid(1e), 3-(methoxycarbonyl)-3-

cyclohexylidenepropanoic acid (1f), (2E,3Z)-3-(methoxycarbonyl)-2-benzylidenepent-3-

enoic acid(1g), (2Z,3E)-2-benzylidene-3-((furan-2-yl)methylene)succinic acid(1h),

Ciprofloxacin(1i), (2E,3Z)-3-(methoxycarbonyl)-2-((furan-2-yl)methylene)pent-3-enoic

acid(1j), (2Z,3E)-3-benzylidene-2-((furan-2-yl)methylene)-4-oxopentanedioic acid(1k),

(4S)-6-chloro-4-(2-cyclopropylethynyl)-4-(trifluoromethyl)-2,4-dihydro-1H-3,1-benzoxazin-

2-one(1l), Norfloxacin(1m), (E)-2-(methoxycarbonyl)-3-methylpent-2-enoic acid(1n), 1S17

ligand(S-form)(1o) , (Z)-3-(methoxycarbonyl)-2-(dicyclohexylmethylene)-4-(furan-2-yl)but-

3-enoic acid(1p), (R)-N-hydroxy-2-(3-oxo-3,4-dihydro-2H-benzo[b][1,4]thiazin-2-yl)

acetamide or Ligand of 1S17(1q) appear in Table2.

The perusal of the Table-2 reveals that the commonly used antibiotic ofloxacin has the

highest docking scores with both the target proteins. The drug candidate (1b) has a docking

score higher than the ligand co-crystallized with 1BSK i,e 1(c) when docked with the protein

1S17 , but lower with the protein 1BSK 1(b). The succinic acid derivatives 1(d)-1(h) have

docking scores with protein 1S17 higher than Ciprofloxacin and norfloxacin but lower than

ofloxacin; but with the protein 1BSK the values of docking scores of 1(b) 1(d) and 1(h) are

higher than ciprofloxacin.

The docking scores of the succinic acid derivatives 1 (b), 1(d) 1(e) 1(f)1(g) 1(h) 1(j) 1(k) 1(n)

and 1(p) are higher than the ligand 1(a). The docking scores of the drug candidates 1(d) to

1(h) lie between ofloxacin and ciprofloxacin, that of drug candidates 1(j) to 1(l) lie between

ciprofloxacin and norfloxacin. The docking scores of remaining candidates are lower than

norfloxacin. The drug candidate 1(b) has the strongest binding with the target protein 1S17,

while 1(k) has the strongest binding with the target protein 1BSK followed closely by 1(l),

1(b), 1(h) and 1(d)

The results of toxicity study namely LC50, LD50 and EC50 appear in Table-2. It is apparent

that all the drug candidates have less virtual toxicity than ciprofloxacin- a widely used

antibiotic.


1319


The druggability of 1(a), 1(b), 1(c),1(d),1(e),1(f),1(g), 1(h),1(i),1(m),1(o) have been

evaluated by quick prop program and the reports appears in the Table3a and 3b. From the

Table it is clear that all these compounds are good drug candidates. There similarities with

other drugs have been tabulated in Table4. The interaction diagram of all the investigated

succinic acid derivatives and well known antibiotics with the proteins 1BSK and 1S17 have

been shown in figure 1a and 1b respectively.

Ligand interaction diagrams (Fig1a and 1b) reveal that the most of the interacting amino

acids in the target proteins are common in cases of both the originally docked ligands and the

drug candidates having highest docking scores with 1BSK and 1S17 have been shown in

figure 2a and 2b respectively.


1320


Table 2. Results of LD50, LC50, EC50 and Docking scores of succinic acid derivatives and well known antibiotics on protein 1BSK and 1S17 .

ligand

DockingScore DockScore

Computed Rat

Inhalational LC50

Computed Rat oral

LD50

Assesment of

Daphnia EC50

1BSK 1S17 Mg/m3/H g/kg Ofloxacin (1a) -9.33 -10.51 64.8 1.5 77.0 3-(methoxycarbonyl)-4,4-diphenylbut-3-enoic acid(1b) -8.81 -9.68 5.6 2.1 34.7 1BSKligand(1c) -9.85 -9.64 10.6 1.1 0 2-(diphenylmethylene)succinic acid(1d) -8.23 -9.23 3.4 2.1 2.1 (2E,3Z)-3-(methoxycarbonyl)-2-((furan-2-yl)methylene)-4-phenylbut-3-enoic acid(1e)

-8.85 -9.19 5.8 8.5 47.9

3-(methoxycarbonyl)-3-cyclohexylidenepropanoic acid(1f) -7.87 -9.07 10.0 4.9 46.4 (2E,3Z)-3-(methoxycarbonyl)-2-benzylidenepent-3-enoic acid(1g) -6.7 -9.06 2.2 5.1 73.1 (2Z,3E)-2-benzylidene-3-((furan-2-yl)methylene)succini96c acid(1h) -8.73 -8.7 4.0 2.1 3.2 Ciprofloxacin(1i) -8.70 -8.66 1.1 1.1 1.3 (2E,3Z)-3-(methoxycarbonyl)-2-((furan-2-yl)methylene)pent-3-enoic acid(1j) -7.87 -8.57 10.0 5.9 269.0 (2Z,3E)-3-benzylidene-2-((furan-2-yl)methylene)-4-oxopentanedioic acid(1k) -8.91 -8.05 4.9 1.5 7.4 (4S)-6-chloro-4-(2-cyclopropylethynyl)-4-(trifluoromethyl)-2,4-dihydro-1H-3,1-benzoxazin-2-one(1l)

-7.13 -7.87 10.0 814.9 624.9

Norfloxacin(1m) -7.87 -7.49 2.1 617.3 39.3 (E)-2-(methoxycarbonyl)-3-methylpent-2-enoic acid(1n) -5.88 -7.01 10.0 653.7 0.0 1S17 ligand(S-form)(1o) -6.97 -6.99 322.9 10.0 5.9 (Z)-3-(methoxycarbonyl)-2-(dicyclohexylmethylene)-4-(furan-2-yl)but-3-enoic acid(1p)

-7.86 -6.72 6.8 5.4 1.1

(R)-N-hydroxy-2-(3-oxo-3,4-dihydro-2H-benzo[b][1,4]thiazin-2-yl)acetamide or Ligand of 1S17(1q)

-6.8 -6.64 322.9 10.0 5.9


1321


Table2a. QuickProp properties of inhibitor of IBSK, 1S17 and antibiotics Ofloxacin, Norfloxacin, Ciprofloxacin

1(c) 1(o) 1(a) 1(m) 1(i) Range Solute Molecular Weight 429.409 238.261 361.372 319.335 347.345 ( 130.0 / 725.0) Solute Total SASA 722.038 430.621 584.174 547.144 554.634 ( 300.0 /1000.0)

Solute Hydrophobic SASA 347.049 45.171 349.367 284.433 287.412 ( 0.0 / 750.0) Solute Hydrophilic SASA 191.796 187.088 146.727 169.718 166.456 ( 7.0 / 330.0) Solute Carbon Pi SASA 141.604 166.611 61.237 67.149 74.331 ( 0.0 / 450.0)

Solute Weakly Polar SASA 41.589 31.751 26.843 25.844 26.435 ( 0.0 / 175.0) Solute Molecular Volume (A^3) 1312.042 707.528 1039.2 953.682 991.487 ( 500.0 /2000.0)

Solute vdW Polar SA (PSA) 143.867 101.737 87.636 92.941 102.98 ( 7.0 / 200.0) Solute No. of Rotatable Bonds 14 3 1 2 1 ( 0.0 / 15.0)

Solute as Donor - Hydrogen Bonds 3.25 3 0 1 2 ( 0.0 / 6.0) Solute as Acceptor - Hydrogen Bonds 5.25 7.2 7.25 6 7.5 ( 2.0 / 20.0)

Solute Globularity (Sphere = 1) 0.803 0.892 0.849 0.856 0.867 ( 0.75 / 0.95) QP Polarizability (Angstroms^3) 38.717 21.826 35.378M 31.369M 33.593M ( 13.0 / 70.0) QP log P for hexadecane/gas 13.826 8.227 9.170M 8.808M 9.462M ( 4.0 / 18.0)

QP log P for octanol/gas 20.847 16.148 16.837M 16.254M 19.053M ( 8.0 / 35.0) QP log P for water/gas 11.537 16.497 9.470M 9.589M 12.797M ( 4.0 / 45.0)

QP log P for octanol/water 4.308 -0.815 -0.383 -0.988 -0.387 ( -2.0 / 6.5) QP log S for aqueous solubility -4.631 -0.829 -2.891 -3.371 -3.362 ( -6.5 / 0.5)

QP log S - conformation independent -5.347 -1.353 -3.086 -2.978 -2.765 ( -6.5 / 0.5) QP log K hsa Serum Protein Binding -0.248 -1.001 -0.508 -0.174 -0.254 ( -1.5 / 1.5)

QP log BB for brain/blood -2.163 -1.108 -0.388 -0.638 -0.51 ( -3.0 / 1.2) No. of Primary Metabolites 3 4 1 1 0 ( 1.0 / 8.0)

Predicted CNS Activity (-- to ++) -- -- +/- +/- +/-

HERG K+ Channel Blockage: log IC50 -0.41 -2.704 -3.18 -3.095 -2.957 (concern below -5)

Apparent Caco-2 Permeability (nm/sec) 7 89 25 15 16 (<25 poor, >500

great) Apparent MDCK Permeability

(nm/sec) 8 106 18 10 11

(<25 poor, >500 great)

QP log Kp for skin permeability -3.211 -4.093 -5.975 -6.281 -6.292 (Kp in cm/hr)


1322


Jm, max transdermal transport rate 0.006 2.852 0 0 0 (micrograms/cm^2-

hr) Lipinski Rule of 5 Violations 0 0 0 0 0 (maximum is 4)

Jorgensen Rule of 3 Violations 1 0 0 1 1 (maximum is 3) % Human Oral Absorption in GI (+-

20%) 68 57 50 42 46 (<25% is poor)

Qual. Model for Human Oral Absorption

Medium Medium Medium Medium Medium (>80% is high)

Table 2b.quickProp properties succinic acid derivatives

1(b) 1(d) 1(e) 1(f) 1(g) 1(h) Range

Solute Molecular Weight 296.322 282.295 298.295 212.245 246.262 284.268 ( 130.0 / 725.0)

Solute Total SASA 514.911 494.617 533.126 443.046 477.775 485.138 ( 300.0 /1000.0)

Solute Hydrophobic SASA 87.997 15.536 105.082 290.132 186.551 15.094 ( 0.0 / 750.0)

Solute Hydrophilic SASA 136.008 161.598 117.349 150.936 118.428 158.177 ( 7.0 / 330.0)

Solute Carbon Pi SASA 290.906 317.483 310.695 1.978 172.795 311.867 ( 0.0 / 450.0)

Solute Weakly Polar SASA 0 0 0 0 0 0 ( 0.0 / 175.0)

Solute Molecular Volume (A^3) 907.927 857.085 919.726 737.532 811.147 840.393 ( 500.0 /2000.0)

Solute vdW Polar SA (PSA) 75.371 87.786 73.638 79.427 69.686 88.528 ( 7.0 / 200.0)

Solute No. of Rotatable Bonds 6 6 7 3 5 7 ( 0.0 / 15.0) Solute as Donor - Hydrogen Bonds 1 2 1 1 1 2 ( 0.0 / 6.0) Solute as Acceptor - Hydrogen Bonds 4 4 4.5 4 4 4.5 ( 2.0 / 20.0)

Solute Globularity (Sphere = 1) 0.881 0.882 0.858 0.891 0.88 0.888 ( 0.75 / 0.95) QP Polarizability (Angstroms^3) 29.107M 27.326M 29.126M 21.455M 24.748M 25.962M ( 13.0 / 70.0)


1323


QP log P for hexadecane/gas 9.983M 10.095M 9.998M 6.435M 8.078M 9.901M ( 4.0 / 18.0) QP log P for octanol/gas 14.135M 15.042M 13.840M 11.291 12.06 14.705M ( 8.0 / 35.0) QP log P for water/gas 7.943M 9.714M 8.267M 6.568 7.151 9.901M ( 4.0 / 45.0)

QP log P for octanol/water 3.23 3.131 3.246 1.654 2.609 2.87 ( -2.0 / 6.5) QP log S for aqueous solubility -3.278 -2.859 -3.266 -2.531 -2.798 -2.423 ( -6.5 / 0.5)

QP log S - conformation independent -4.355 -4.011 -4.144 -2.017 -3 -3.819 ( -6.5 / 0.5) QP log K hsa Serum Protein Binding -0.08 -0.414 -0.193 -0.393 -0.292 -0.566 ( -1.5 / 1.5)

QP log BB for brain/blood -0.967 -1.182 -0.921 -0.885 -0.756 -1.196 ( -3.0 / 1.2) No. of Primary Metabolites 1 1 1 3 1 1 ( 1.0 / 8.0)

Predicted CNS Activity (-- to ++) - -- - - - --

HERG K+ Channel Blockage: log IC50 -3.043 -1.337 -3.505 -1.497 -2.484 -1.221 (concern below -5)

Apparent Caco-2 Permeability (nm/sec) 128 18 193 92 188 20 (<25 poor, >500 great)

Apparent MDCK Permeability (nm/sec) 68 10 106 48 103 11 (<25 poor, >500 great)

QP log Kp for skin permeability -2.425 -2.803 -1.916 -4.006 -2.613 -2.664 (Kp in cm/hr)

Jm, max transdermal transport rate 0.586 0.614 1.962 0.062 0.955 2.327 (micrograms/

cm^2-hr)

Lipinski Rule of 5 Violations 0 0 0 0 0 0 (maximum is

4)

Jorgensen Rule of 3 Violations 0 1 0 0 0 1 (maximum is

3)

% Human Oral Absorption in GI (+-20%) = 84 68 87 72 83 67 (<25% is

poor)

Qual. Model for Human Oral Absorption HIGH Medium HIGH HIGH HIGH Medium (>80% is

high)


1324


Table3.Drug most similar to the interested succinic acid derivatives, antibiotics and originally docked ligands and their uses.

ligand Most similar drug % similar Used as Ofloxacin (1a) Rufloxacin 96.28 Antibacterial

3-(methoxycarbonyl)-4,4-diphenylbut-3-enoic acid(1b) Epalrestat 90.75 Effective delay the progression of diabetic neuropathy.

1BSKligand(1c) Limaprost 74.40 vasodilator that increases blood flow and inhibits platelet aggregation

2-(diphenylmethylene)succinic acid(1d) Olsalazine 87.64 Anti-inflammatory, treatment of inflammatory bowel disease

(2E,3Z)-3-(methoxycarbonyl)-2-((furan-2-yl)methylene)-4-phenylbut-3-enoic acid(1e) Epalrestat 89.11

Effective delay the progression of diabetic neuropathy.

3-(methoxycarbonyl)-3-cyclohexylidenepropanoic acid(1f) Captopril 90.67 Treatment of hypertension, heart failure and dibetes.

(2E,3Z)-3-(methoxycarbonyl)-2-benzylidenepent-3-enoic acid(1g) Tranilast 90.80 an anti-allergy drug

(2Z,3E)-2-benzylidene-3-((furan-2-yl)methylene)succinic acid(1h) Olsalazine 83.91 Anti-inflammatory treatment of inflammatory bowel disease.

Ciprofloxacin(1i) Grepafloxacin 87.31 antibacterial agent

(2E,3Z)-3-(methoxycarbonyl)-2-((furan-2-yl)methylene)pent-3-enoic acid(1j) Ethamivan 90.42

Treatment of barbiturate overdoseand chronic obstructive pulmonary disease,

(2Z,3E)-3-benzylidene-2-((furan-2-yl)methylene)-4-oxopentanedioic acid(1k) Balsalazide 84.53 anti-inflammatory drug (4S)-6-chloro-4-(2-cyclopropylethynyl)-4-(trifluoromethyl)-2,4-dihydro-1H-3,1-benzoxazin-2-one(1l) Zaltoprofen 86.44

Analgesic, antipyretic and anti-inflammatory agent Non-steroidal anti-inflammatory drug,

Norfloxacin(1m) Enoxacin 96.82 treatment of urinary tract infections and gonorrhea. Insomnia

(E)-2-(methoxycarbonyl)-3-methylpent-2-enoic acid(1n) Mechlorethamine 83.49 treat Hodgkin lymphoma, non Hodgkin lymphoma, lung cancer

1S17 ligand(S-form)(1o) Emtricitabine 85.49 treatment of HIV infection (Z)-3-(methoxycarbonyl)-2-(dicyclohexylmethylene)-4-(furan-2-yl)but-3-enoic acid(1p) Estradiol 86.73

Treatment of menopause , breast cancer and prostate cancer

(R)-N-hydroxy-2-(3-oxo-3,4-dihydro-2H-benzo[b][1,4]thiazin-2-yl)acetamide or Ligand of 1S17(1q) Emtricitabine 85.47 treatment of HIV infection r


1325


Fig1a. Interaction diagram of the docked ligands (1a-1k) in 1BSK

Fig. 1(a)

Fig.1(b) Fig.1(c)

Fig.1(d)

Fig.1(e)

Fig.1(f)


1326


Fig. 1(g)

Fig.1(h)

Fig.1(i)

Fig. 1(j)

Fig.1(k)

Fig.1(l)


1327


Fig.1(m)

Fig.1(n)

Fig.1(o)

Fig.1(p)

Fig.(1q)


1328


Fig1b. Interaction diagram of the docked ligands (1a-1k) in 1S17

Fig.1(a)

Fig.1(b)

Fig.1(c)

Fig.1(d)

Fig.1(e)


1329


Fig.1(g)

Fig.1(h)

Fig.1(i)

Fig.1(j)

Fig.1(k)

Fig.1(l)


1330


Fig.1(m)

Fig.1(n) Fig.1(o)

Fig.1(p)

Fig.1(q)


1331


Table 1. Orientation of selected highest scoring of succinic acid derivatives (1k, green colour) in IBSK having hydrogen bonding with LEU91,GLN50

ILE44 and p-interaction with ARG97.

Figure2b. Orientation of selected highest scoring of succinic acid derivatives(1b-green colour) in IS17 having hydrogen bonding with amino acids

1LE45 and LEU93.


1332


CONCLUSION

The main purpose of this study was to search potentially cheap antibiotics. Some readily

accessible succinic acid derivatives have been found in this study to be virtually more active

and less toxic than widely used antibiotic ciprofloxacin when the molecular docking studies

were carried out against proteins with PDB ID IBSK and ISI7 obtained from E.Coli and

pseudomonas aeruginosa respectively. So, these succinic acid derivatives may be potentially

active against the diseases causes by the micro-organisms E.Coli and pseudomonas

aeruginosa.

ACKNOWLEDGMENT

We are thankful to Will Richard, Raghu Rangaswamy, Vinod Dewarjee for providing the

Shrodinger2012 software.

REFERENCES [1] J. M. Adams, On the Release of the Formyl Group from Nascent Protein, J. Mol. Biol.

1968, 33, 571. [2] Z. Zhou, X. Song, and W. Gong, Novel Conformational States of Peptide Deformylase

from PathogenicBacterium Leptospira interrogans, J. Biol. Chem. 2005, 280, 42391.

[3] C. M. Apfel, H. Locher, S. Evers, B. Takács, C. Hubschwerlen, W. Pirson, M. G. P. Page,

and W. Keck, Peptide Deformylase as an Antibacterial Drug Target: Target Validation

and Resistance Development, Antimicrob. AgentsChemother. 2001, 45, 1058.

[4] D. J. Durand, B. G. Green, J. F. O’Connell, and S. K. Grant, Peptide aldehyde inhibitors

of bacterial peptide deformylases. Arch. Biochem. Biophys.1999, 367, 297.

[5] Y. J. Hu, P. T. Rajagopalan, and D. Pei., H–phosphonate derivatives as novel peptide

deformylase inhibitors.Bioorg. Med. Chem. Lett. 1998, 8, 2479.

[6] T. Meinnel, L. Patiny, S. Ragusa, and S. Blanquet. Design and synthesis of substrate

analogue inhibitors of peptide deformylase. Biochemistry, 1999, 38, 4287.

[7] J. M. Clements, R. P. Beckett, A. Brown, G. Catlin, M. Lobell, S. Palan, W. Thomas, M.

Whittaker, S. Wood, S.Salama, P.J. Baker, H. F. Rodgers, V. Barynin, D. W. Rice, and

M. G. Hunter, Antibiotic Activity and Characterization of BB–3497, a Novel Peptide

Deformylase Inhibitor, Antimicrob. Agents Chemother. 2001, 45,563.

[8] V. Molteni, X. He, J. Nabakka, K. Yang, A. Kreusch, P. Gordon, B. Bursulaya, I. Warner,

T. Shin, T. Biorac, N.S. Ryder, R. Goldberg, J. Doughty, and Y. He, Identification of

novel potent bicyclic peptide deformylase inhibitors, Bioorg. Med. Chem. Lett. 2004, 14,

1477.


1333


[9] D. Z. Chen, D. V. Patel, C. J. Hackbarth, W. Wang, G. Dreyer, D. C. Young, P. S.

Margolis, C. Wu, Z. J. Ni, J. Trias, R. J. White, and Z. Y. Yuan. Actinonin, a naturally

occurring antibacterial agent, is a potent deformylase inhibitor. Biochemistry 2000,

39,1256.

[10] C. Apfel, D. W. Banner, D. Bur, M. Dietz, T. Hirata, C. Hubschwerlen, H. Locher, M.

G. Page, W. Pirson, G.Rosse, and J. L. Specklin. Hydroxamic acid derivatives as potent

peptide deformylase inhibitors and antibacterial agents. J. Med. Chem. 2000, 43, 2324.

[11] Hao, B., Gong, W., Rajagopalan, P.T., Zhou, Y., Pei, D., Chan, M.K

Structural basis for the design of antibiotics targeting peptide deformylase J. PubMed

1999, 38, 4712-4719

[12] Molteni, V., He, X., Nabakka, J., et al., Goldberg, R., Doughty, J., and He, Y.

Identification of novel potent bicyclic peptide deformylase inhibitors, Bioorg Med Chem

Lett, 2004, 14, 1477-1481

IN SILICO SEARCH OF SOME CHEAP ANTIBIOTICS-PART-1

Documents

Transcript of IN SILICO SEARCH OF SOME CHEAP ANTIBIOTICS-PART-1