Non-peptidic Thrombospondin-1 Mimics as Fibroblast Growth Factor-2 Inhibitors: AN INTEGRATED...

Non-peptidic Thrombospondin-1 Mimics as FibroblastGrowth Factor-2 InhibitorsAN INTEGRATED STRATEGY FOR THE DEVELOPMENT OF NEW ANTIANGIOGENICCOMPOUNDS*□S

Received for publication, November 16, 2009, and in revised form, December 24, 2009 Published, JBC Papers in Press, January 7, 2010, DOI 10.1074/jbc.M109.085605

Giorgio Colombo‡, Barbara Margosio§, Laura Ragona¶, Marco Neves‡, Silvia Bonifacio§, Douglas S. Annis�,Matteo Stravalaci**, Simona Tomaselli¶, Raffaella Giavazzi§, Marco Rusnati‡‡, Marco Presta‡‡, Lucia Zetta¶,Deane F. Mosher�, Domenico Ribatti§§, Marco Gobbi**, and Giulia Taraboletti‡1

From the ‡Istituto di Chimica del Riconoscimento Molecolare, Consiglio Nazionale delle Ricerche, Milan 20131, Italy, the§Department of Oncology, Mario Negri Institute for Pharmacological Research, Bergamo 24125, Italy, the ¶Istituto per lo Studiodelle Macromolecole, Consiglio Nazionale delle Ricerche, Milan 20133, Italy, the �Departments of Biomolecular Chemistry andMedicine, University of Wisconsin, Madison, Wisconsin 53706, the **Department of Biochemistry and Molecular Pharmacology,Mario Negri Institute for Pharmacological Research, Milan 20156, Italy, the ‡‡Department of Biomedical Sciences andBiotechnology, School of Medicine, University of Brescia, Brescia 25123, Italy, and the §§Department of Human Anatomy andHistology, University of Bari, Bari 70124, Italy

Endogenous inhibitors of angiogenesis, such as throm-bospondin-1 (TSP-1), are promising sources of therapeuticagents to treat angiogenesis-driven diseases, including cancer.TSP-1 regulates angiogenesis through different mechanisms,including binding and sequestration of the angiogenic factorfibroblast growth factor-2 (FGF-2), through a site located in thecalcium binding type III repeats. We hypothesized that theFGF-2 binding sequence of TSP-1 might serve as a template forthe development of inhibitors of angiogenesis. Using a peptidearray approach followed by binding assays with synthetic pep-tides and recombinant proteins, we identified a FGF-2 bindingsequence of TSP-1 in the 15-mer sequence DDDDDNDKIPD-DRDN. Molecular dynamics simulations, taking the full flexi-bility of the ligand and receptor into account, and nuclearmagnetic resonance identified the relevant residues and confor-mational determinants for the peptide-FGF interaction. Thisinformation was translated into a pharmacophore model usedto screen the NCI2003 small molecule databases, leading to theidentification of three small molecules that bound FGF-2 withaffinity in the submicromolar range.The lead compounds inhib-ited FGF-2-induced endothelial cell proliferation in vitro andaffected angiogenesis induced by FGF-2 in the chicken cho-rioallantoic membrane assay. These small molecules, therefore,represent promising leads for the development of antiangio-genic agents. Altogether, this study demonstrates that newbiological insights obtained by integrated multidisciplinaryapproaches can be used to develop small molecule mimics ofendogenous proteins as therapeutic agents.

Inhibitors of angiogenesis, aimed at preventing the deregu-lated formation of new blood vessels, are emerging as a success-ful approach to treat an array of diseases, including cancer (1).Antiangiogenic strategies are designed to reestablish the bal-ance between angiogenic factors and endogenous inhibitors,restoring the physiologically quiescent condition of the vascu-lature (2). A strategy to achieve this is to exploit the activity ofendogenous inhibitors of angiogenesis (3).Thrombospondin-1 (TSP-1)2 was the first endogenous

inhibitor of angiogenesis identified (4, 5). Of the five membersthat constitute the TSP family in mammals, the homotrimericTSP-1 and TSP-2 share domain organization and the ability toinhibit angiogenesis. Like other thrombospondins, TSP-1 is amulti-modular protein. Eachmonomer consists of an N-termi-nal globular domain followed by the coiled-coil oligomerizationdomain, a von Willebrand factor type C repeat, three proper-din-like type I repeats, two TSP-type epidermal growth factor(EGF)-like or type II repeats, and a signature domain compris-ing a third EGF-like repeat, the calcium binding wire or type IIIrepeats, and the lectin-like C-terminal globular domain (6).TSP-1 has been classified functionally as a matricellular pro-

tein, i.e. an extracellular protein that acts to regulate cell inter-actions with the environment (7). TSP-1 binds to a variety ofproteins on the cell surface and in the extracellularmilieu. EachTSP-1 domain has a distinct complement of bindingmolecules,and TSP-1 can elicit different functions, depending on whichdomain is active and able to engage its specific cell receptorsand extracellular ligands. It is, therefore, not surprising thatTSP-1 can exert its antiangiogenic activity through multiplemechanisms involving different active sequences in differentdomains (8, 9).The main antiangiogenic site of TSP-1 has been identified in

the type I repeats and includes adjacent sequences that interact* This work was supported in part by National Institutes of Health Grant

HL054462, the Associazione Italiana per la Ricerca sul Cancro, FondazioneCariplo, and the Italian Ministry of Health (GR2007 and onc_ord 25/07), andEuropean Union IP-FP7-HEALTH-2007-ADAMANT, 201342.

□S The on-line version of this article (available at http://www.jbc.org) containssupplemental Figs. 1–3, Tables 1–3, and “Methods.”

1 To whom correspondence should be addressed: Mario Negri Institute forPharmacological Research, via Gavazzeni, 11, 24125 Bergamo, Italy. E-mail:[email protected].

2 The abbreviations used are: TSP-1, thrombospondin-1; FGF-2, fibroblastgrowth factor-2; HSPG, heparan sulfate proteoglycans; EGF, epidermalgrowth factor; MD, molecular dynamics; SPR, surface plasmon resonance;RU, resonance units; STD, saturation transfer difference.

THE JOURNAL OF BIOLOGICAL CHEMISTRY VOL. 285, NO. 12, pp. 8733–8742, March 19, 2010© 2010 by The American Society for Biochemistry and Molecular Biology, Inc. Printed in the U.S.A.

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with the CD36 receptor, transforming growth factor-� andheparan sulfate proteoglycans (HSPGs). Other sequences indifferent domains of TSP-1 influence angiogenesis throughbinding to angiogenic growth factors, integrins, CD47, HSPG,proteases, and low density lipoprotein receptor-related pro-teins (for review, see Refs. 10 and 11). Recently, using recombi-nant portions of TSP-1, we identified a previously undescribedantiangiogenic site in the type III repeats of TSP-1 and demon-strated that binding of the angiogenic factor FGF-2 to this siteinhibits angiogenesis by sequestration of FGF-2 (12). Binding ofFGF-2 to TSP-1 and its type III repeats is of high affinity andinvolves a yet unidentified sequence sensitive to calcium andheparin (12–14). Each antiangiogenic TSP-1 sequence offers apotential tool for the design of new angiogenesis inhibitors (10,15), as exemplified by ABT-510, a synthetic nonapeptide basedon the sequence GVITRIR in the second type I repeat that wasthe first TSP-1-based antiangiogenic compound to reach clini-cal testing (16).Protein-protein interactions are generally difficult to inhibit

with small molecules because of their large, flexible surfaces,which pose a fundamentally different problem from targetingsmall, well defined concave active sites (17, 18). The use of abiologically relevant, functional peptide sequence as an entrypoint for lead development represents a potential powerfulapproach in drug discovery (19–22). The starting sequence canelucidate the roles of key interactions (hot spots) involved in theregulation/inhibition of important protein-protein interac-tions that a synthetic molecule must mimic. The knowledge ofrelevant interactions and their space relationships in the stabi-lization of protein�protein complexes may thereby boost ourability to interfere with specific protein-protein interactions,providing attractive therapeutic opportunities and extendingmedicinal chemistry to new classes of compounds. Differentrational approaches are in fact based on the identification ofsynthetic molecules that mimic the hot spot interactions in rel-evant macromolecular complexes (20, 23, 24). Computationalbiology methods based on all-atom molecular dynamics (MD)have recently proved successful in identifying the functionaland conformational determinants ofmolecular recognition andtranslating these models into novel antagonists with specificactivities, thus expanding the molecular diversity space ofmimics of interacting active sequences (25–29). This studyaimed at identifying the FGF-2-binding sequence of theTSP-1 type III repeats and used an approach integratingcomputational biology, biophysics, biochemistry, and func-tional biology to design new, non-peptidic inhibitors ofangiogenesis based on this sequence.

EXPERIMENTAL PROCEDURES

Reagents—Sequences of peptides used in the study are indi-cated in Table 1. Peptides (biotin-labeled or acetylated at the Nterminus) were obtained from Pepscan Presto BV (Lelystad,The Netherlands) or were synthesized by R. Longhi (ConsiglioNazionale delle Ricerche, Milan, Italy). At least two batchesof the peptides DD15, DIDG16, AQ19, and DD35 were tested.The small molecules were obtained from the DevelopmentalTherapeutics Program, NCI, National Institutes of Health(Rockville, MD). Preparation of recombinant human TSP-1

fragments (30) is described in the supplemental Methods.Human recombinant FGF-2 (R&D Systems, Minneapolis, MN)was obtained through the NCI-Biological Resources Branch(Frederick, MD). For the NMR studies, human recombinantFGF-2 was kindly provided by A. Bikfalvi (University of Bor-deaux). Proteins were labeled with biotin or the lanthanideeuropium, as described in the supplemental Methods.Peptide Array Analysis—A peptide array was designed based

on the sequence of the type III repeats. Peptides were synthe-sized and screened by Pepscan Presto as described previously(31). Briefly, 237 20-mer peptides with partially overlappingsequences (19-amino acid overlaps) were synthesized andcovalently linked to polypropylene cards. The binding of bio-tinylated FGF-2 (10 �g/ml) to the peptides was tested. BoundFGF-2 was detected with peroxidase-conjugated streptavidinand the peroxidase substrate 2,2�-azino-di-3-ethylbenzthiazo-line sulfonate (ABTS). Color development was quantified witha CCD camera (Sony CCD Video Camera XC-77RR) and theimage processing software Optimas 6.5 (Media Cybernetics,Silver Spring, MD). Data are presented as the relative signalvalue, calculated by normalizing each value Sn to an arbitrarilyset background value Sbckg and to the maximal signal Smax:(Sn � Sbckg)/(Smax � Sbckg).Binding Assays—The peptide-FGF-2 interaction was

assessed as direct binding of the biotin-labeled peptides tomicrotiter plates coated with FGF-2, as described in the sup-plemental Methods. Bound peptide was detected by mouseanti-biotin antibody and mouse IgG Elite Vectastain ABC kit(Vector Laboratories) followed by 1,2-phenylenediaminedihydrochloride (Dako, Glostrup, Denmark) as a chromogen. Asimilar procedure was used to assess the binding of biotin-la-beled FGF-2 to recombinant TSP-1 domains and to analyze theability of small molecules to inhibit the binding of the biotin-labeled recombinant type III domain to FGF-2. See the supple-mental Methods for detailed protocols.

Kinetic binding constants and affinity values were obtainedby using surface plasmon resonance (SPR), carried out with theProteOn XPR36 Protein Interaction Array system (Bio-Rad)(32). FGF-2 was covalently immobilized on the sensorchip(ProteonGLCBio-Rad) by amine coupling chemistry, with finalimmobilization levels of 3500–4000 resonance units (RU; 1RU � 1 pg of protein/mm2). A reference surface was alwaysprepared in parallel with no ligand immobilized. Peptides andsmall molecules were then injected over immobilized FGF-2 ata rate of 30 �l/min for 3 min (association phase), whereas dis-sociation was measured in the following 10–15 min. The run-ning buffer, also used to dilute analytes, was phosphate-buff-ered saline, pH 7.4, 0.005%Tween 20 (Bio-Rad). All these assayswere done at 25 °C.The sensorgrams (time course of the SPR signal in RUs) were

normalized to a base-line value of 0. The signal observed in thesurfaces immobilizing FGF-2 was corrected by subtractingthe nonspecific response observed in the reference surface. Theresulting sensorgrams were fitted by the simplest 1:1 interac-tion model (Langmuir model, ProteOn analysis software) toobtain the corresponding association and dissociation rate con-stants (Kon and Koff) and the equilibrium dissociation constant

Non-peptidic TSP-1 Mimics as FGF-2 Inhibitors

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Kd (Koff/Kon). Details are provided in the supplementalMethods.Simulation SetUpandAnalysis—Simulations forDD15were

started from a fully extended conformation of the peptide toeliminate possible conformational biases. An initial represent-ative conformation for the peptide was obtained by conforma-tional search using the Systematic Unbounded Multiple Mini-mum (SUMM) routine implemented in MACROMODELVersion 8.1 with the AMBER force field and the Polak-RibiereConjugate Gradient (PRCG)minimizationmethodwith amax-imum of 700 minimization steps and an energy convergencecriterion of 0.05 kJ/mol. Solvent effects were taken into accountby using the Generalized Born/Surface Area (GB/SA) explicitsolvent model with a dielectric constant � of 78 (33). The globalminimum conformation obtained from this preliminary calcu-lation was then subjected to 60 ns of MD refinement in explicitwater solvent using the same protocol as described in the nextparagraph for MD simulations of the complexes. The resultingtrajectories were analyzed by the structural clustering methoddescribed by Daura et al. (34). The most representative struc-tures of DD15 obtained after cluster analysis of the trajectorywere subjected to multiple docking runs on the surface ofFGF-2 (x-ray structure downloaded from the PDB code 1fq9)using the programAUTODOCK (35) essentially as described inMeli et al. (25) and Plescia et al. (36). The representative struc-ture of the most populated cluster obtained from the dockingruns, corresponding also to the free energyminimum, was usedfor successive MD refinement. The structural evolution ofDD15 in isolation and of the complex DD15�FGF-2 was studiedwith long time scale MD simulations in explicit water solvent.DD15 or the DD15�FGF-2 complex was first solvated withwater in a periodic-truncated octahedron large enough to con-tain the peptide or complexes and 0.8 nm of solvent on all sides.The protonation and charge states of the side chains of thepeptides and the receptor were chosen to be consistent withthe solution conditions of the experiments; amine groups wereconsidered as having a �1 charge, and carboxylic groups wereconsidered as having a �1 charge. The FGF/DD15 system wasfound to have a total charge of �4 (FGF �11/DDD �7). FourCl� counter ions were added to the system to ensure electro-neutrality. The system was initially energy-minimized with asteepest descent method for 5000 steps. The temperature wasmaintained close to the intended value of 300 K by weak cou-pling to an external temperature bath. The GROMOS96 forcefield and the simple point charge water model were used. Thecalculation of electrostatic forces utilized the particle meshEwald implementation of the Ewald summation method.MolecularDynamics stimulationswere run at constant numberof particles, volume, and temperature (NVT ensemble) andwere 60 ns long. All the MD runs and the analysis of the trajec-tories were performed using the GROMACS software package.Configurations of the receptor�ligand complex were savedevery 4 ps for subsequent statistical analysis.More complete descriptions of the simulation and docking

methodologies are detailed in the supplemental Methods. Forthe sake of simplicity the numbering of FGF-2 starts from 1(residue 16 in the original Protein Data Bank file).

Nuclear Magnetic Resonance (NMR) Spectroscopy—A set oftwo-dimensional NMR experiments (TOCSY, ROESY, NOESY)was used to assign the proton chemical shifts of DD15 dissolvedat 0.7 mM peptide concentration in 30 mM water phosphatebuffer, 50 mM NaCl, pH 7. NMR spectra were recorded on aBrukerDMX500MHzNMRspectrometer. T1,measured in thepresence of FGF-2, were found to be rather constant along thepeptide side chains in a range of 0.5–0.8 s, except for a longerT1value measured for methyl protons of acetylic group (1.3 s).The DD15 chemical groups involved in the direct contact

with FGF-2 were identified by saturation transfer difference(STD) methods. One-dimensional STD pulse sequence incor-porating a T1� filter to remove disturbing protein signals wasused (37). On-resonance irradiations were performed at differ-ent frequencies in the methyl (�236 Hz) and aromatic (3,220Hz) regions, and off resonance irradiation was performed at�15,000Hzusing a series ofGaussian pulseswith a 1% truncationand50-msduration togivedifferent total saturation timesof2, 2.5,3, 4, and 4.5 s. See the supplemental Methods for details.Pharmacophore Generation—The central structure of the

most populated cluster for the DD15�FGF-2 complex obtainedfromMD simulations was used as a template to direct pharma-cophore design. The relative distances and orientations (dihe-dral angles) among the different groups of DD15 identified asresponsible for the most persistent interactions with FGF-2fromMDwere used to define the pharmacophoric points. Cat-alyst software (AccelrysCatalyst, SanDiegoCA, 2005)was usedfor pharmacophore design. The models created were used toscreen the NCI, National Institutes of Health data base. The listof compounds retrieved was post-processed using drug-like-ness filters. See the supplemental Methods for details.Biological Assays—The biological activity of the small mole-

cules was analyzed as the ability to prevent the binding of euro-pium-labeled FGF-2 to bovine aortic endothelial cells, mea-suring bound FGF-2 by time-resolved fluorescence using aVictormultilabel plate reader (PerkinElmer Life Sciences). Pro-liferation of endothelial cells exposed to 5 ng/ml FGF-2 in thepresence of the small molecules was assessed with a colori-metric assay (14). One small molecule (sm27) was also testedfor ability to affect angiogenesis in the chicken embryo cho-rioallantoic membrane assay using fertilized White Leghornchicken eggs, where angiogenesis is induced by sterilized gelatinsponges loaded with FGF-2 with or without the small molecule(38). Details are described in the supplemental Methods.

RESULTS

Identification of a FGF-2 Binding Sequence of TSP-1—Thepeptide array technology was used to identify linear sequencesinvolved in the interaction of FGF-2 with the type III repeats ofTSP-1. The array consisted of 237 partially overlapping20-mers peptides spanning the entire sequence of the type IIIrepeats (residues 692–945). The immobilized peptides weretested for their ability to bind biotinylated FGF-2. Three poten-tially active sequences were identified: DDDDDNDKIPD-DRDN (residues 739–753; hereafter named DD15), AQYDY-DRDD (761–769; AQ9), and DIDGDG (residues 800–805,DIDG6, Fig. 1a). Biotin-labeled peptides corresponding to thethree candidate sequences were then synthesized and tested for



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the ability to bind FGF-2. In the case of AQ9 and DIDG6, pep-tides were synthesized corresponding to the peak sequencealone or extended to the two closest cysteines (respectively,755–773, AQ19, and 798–812, DIDG15) (Table 1). Only DD15bound FGF-2 (Fig. 1b).

SPR was used to characterize the binding parameters. Fig. 1cshows a representative sensorgram overlay indicative of dose-dependent binding of DD15 to FGF-2. From the sensorgramswe determined the association rate (Kon, 19.7 � 2.0 M�1s�1)and the dissociation rate (Koff, 5.5 � 0.8 � 10�4 s�1) (means �S.E., n � 6), with a Kd of 28.0 �M (Table 2). In agreement withthe above results, no binding was observed with AQ19 peptideup to 30 �M (Table 2).

DD15 is part of calcium binding repeat 3C. To assess thefunctional role of the DD15 sequence in the context of a larger

protein, we used four recombinantTSP-1 constructs starting from thethird EGF-like repeat (residue 648)and covering progressively longersegments of the type III repeats (Fig.1a). Consistent with the experi-ments with synthetic peptides, Tr3(the shortest construct that includesthe DD15 sequence) bound FGF-2,whereas the shorter proteins Tr1and Tr2, lacking this sequence, didnot (Fig. 1d). Tr4 (residues 648–776), comprising both sequences ofDD15 and AQ19, had even higherbinding activity, suggesting co-in-volvement of the two sequences. Inagreement with this, the syntheticpeptide DD35 (residues 739–773)that extended theDD15 sequence toinclude AQ19 (Table 1) showedhigher affinity for FGF-2 due to alower dissociation rate than DD15(Table 2) Thus, the AQ19 sequence,although not directly able to bindFGF-2, might have a stabilizing orsupportive effect on DD15 bindingto FGF-2.MD Analysis of DD15 and the

DD15�FGF-2 Complex, Character-ization of the Binding Interface, andIdentification of Critical Residues—The conformational dynamics ofDD15 in isolation in solution wasstudied by 60-ns-long all-atom,explicit solvent MD simulations.The dominant structure for thepeptide was extended, maximizingthe interactions between the largenumber of charged residues and thewater solvent. This conformation,accounting for about 80% of struc-tures visited, was chosen formultipleblind docking experiments with the

FGF-2protein.The initial free energyminimum, also representingthe most populated structural cluster, for the DD15�FGF-2 com-plexwas further refined through long timescaleMDsimulations inexplicit water. This dockingMD refinement protocol proved suc-cessful in characterizing peptide-protein interfaces and designingnew active peptides (25, 26, 39, 40).The MD-based refinement of the complex aimed at produc-

ing a realistic atomic model for the interaction between DD15and FGF-2. In the simulation, the peptide adopted an extendedconformation over the binding surface of the protein, occupy-ing the heparin-binding site. The interactions stabilizing themost populated conformation were mainly favorable electro-static couplings between the Lys side chains on the surface ofFGF-2 and the negatively chargedAsp groups of DD15 (Fig. 2, aand b). In agreement with the computational model, experi-

FIGURE 1. Identification of the FGF-2 interacting sequence of TSP-1. a, shown is peptide array analysis.Binding of biotin-labeled FGF-2 to the 237 peptides was analyzed and expressed as described under “Experi-mental Procedures.” Shown below the graph is a schematic representation of the structure of the type IIIrepeats, organized in 13 C- or N-type motifs, and of the recombinant fragments Tr1– 4 used in panel d. b, shownis binding of biotin-labeled peptides DD15, AQ9, AQ19, DIDG6, and DIDG15 to immobilized FGF-2. Boundpeptide is expressed as the absorbance (Abs, mean and S.D. of triplicate values). c, shown is SPR analysis of thebinding of DD15 to FGF-2. The figure shows representative sensorgrams obtained by simultaneous injection ofthree concentrations of DD15 (50, 12.5, or 6.25 �M) for 3 min over sensor chip surfaces immobilizing FGF-2. Thecurves could be globally analyzed by the Langmuir equation, modeling a simple bimolecular interaction, andthe corresponding fittings are shown in white. Data are expressed as resonance units versus time. d, shown isbinding of biotin-labeled FGF-2 to the recombinant Tr fragments. Data are the amounts of bound FGF-2, asabsorbance (mean and S.D. of triplicates).



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mental competition binding assays showed that heparin pre-vented DD15 peptide binding to FGF-2 (supplemental Fig. 1),confirming that the peptide and heparin compete for the samebinding site on FGF-2.Analysis of the electrostatic surface potential on the FGF-2

protein did in fact reveal a large positively charged surface atthis site. The large number of Asp residues was crucial in thefinal arrangement ofDD15 on the heparin-binding site (Fig. 2, aand b). Short range hydrophobic interactions also played a rolein stabilizing the final structure of the complex (Fig. 2a). ThePro residue of DD15 optimally packed with the aromatic sidechain of Tyr-9 and the aliphatic part of the side chain of Lys-11from FGF-2. The Ile residue was also involved in contacts withTyr-9 and Arg-29 (supplemental Fig. 2).

Because conformational dynamics and selection play a keyrole in protein-peptide molecular recognition, the statisticaland time-dependent distribution of the interactions betweenfunctional groups of DD15 and the FGF-2 protein was analyzedon the final 30 ns of the MD simulation. This allowed charac-terization of the complex interface while taking account of themotional flexibility of both binding partners. Attention focusedin particular on analysis of hydrogen-bonding, hydrophobic/aromatic, and charge-charge interactions, as these are themost common intermolecular forces determining host/guest(ligand/receptor) recognition in drugs.Several negative ionizable aspartate residues of DD15 were

involved in salt bridges with positively charged residues at theFGF-2 heparin-binding site. At the N terminus of DD15, theinteraction between the side chains of DD15-Asp-741 andFGF-2-Arg-105 was by far the most common charge-chargeinteraction, with 65% permanence within 3 Å followed by Asp-740—Lys-104 (30%) and Asp-745—Arg-105 (21%). At the Cterminus of DD15, DD15-Asp-750 and FGF-2-Arg-29 were in

close proximity for 13% of the last 30 ns of the MD simulation(supplemental Table 1). The functional groups of DD15 in-volved in hydrogen bonding with the heparin-binding siteincluded Asp-750, interacting with FGF-2-Tyr-9, Asp-741,interacting with FGF-2-Arg-105 and FGF-2-Asn-12, Asp-749,interacting with FGF-2-Tyr-9, and Asp-740, interacting withFGF-2-Thr-106 (supplemental Table 2).To define hydrophobic/aromatic interactions, wemonitored

the contacts involving non-polar DD15 side chains, Ile-747 andPro-748, and the FGF-2 protein. These residues interact withvarious amino acids on the surface of FGF-2, namely FGF-2-Tyr-9, FGF-2-Cys-10, FGF-2-Lys-11, FGF-2-Arg-29, and theturn spanning FGF-2-Asn-14—Gly-16 during most of the pro-duction run (supplemental Fig. 2). Solvent-accessible surfaceanalysis revealed that, despite being involved in a large numberof contacts with the protein, DD15-Ile-747 was more exposedto the solvent, whereas DD15-Pro-748 fit nicely into an FGF-2pocket, resulting in much less exposure to the solvent.NMR Analysis of DD15-FGF-2 Interaction—The validity of

the atomic resolution computational model of DD15�FGF-2complex was verified experimentally by NMR-based interac-tion studies. Complete 1H resonance assignment of DD15 waspossible for Asp-745—Arg-751 region (supplemental Table 3),but unambiguous assignment of the N-terminal segment washampered by the large numbers of aspartic and asparagine res-idues and the extensive signal overlap in theNMR spectra. STDNMR methods were recently successful in characterizing theinteraction between FGF-2 and antiangiogenic peptidesderived from natural FGF-2 binders (41–43). The sameapproach was used to investigate the structural basis ofDD15-FGF-2 interactions and map the peptide residues mak-ing direct contact with the protein. STD spectra prove that H�of Lys-746 and methyl H� and H� protons of Ile-747 receivesaturation from the protein (Fig. 3a). The STD signals at 2.70and 2.83 ppm suggest that DD15 interacts with FGF-2 throughthe side-chain protons of aspartic residues, possiblyAsp-741. Inparticular, beta protons of Asp-750 correspond to the signalobserved at 2.70 ppm, although the contribution to the interac-tion of some of the unassigned aspartic residues cannot be ruledout. Altogether the NMR data point to specific contacts mainlyestablished by theC-terminal region of DD15 peptide involvingthe segment Lys-746-Asp-750, recapitulated in Fig. 3b. Addi-tional stabilizing contacts could be established by electrostaticinteractions involving other aspartic side chains of DD15.Pharmacophoric Hypothesis, Small Molecule Identification,

and Binding Analysis—MD and NMR analyses yielded a con-sistent identification of DD15 residues mostly involved in therecognition of FGF-2 and stabilization of the complex. Thisprompted us to search for small molecule mimics, with func-tional and structural features directly related to the DD15 rec-ognition properties at the FGF-2 surface (25). In principle, thesemolecules should be able to interfere with FGF-2 functions atthe cellular level.A pharmacophoric hypothesis (HYP-DD15) was built based

on the results of the MD simulation, validated by NMR data,which indicated that both hydrophobic and electrostatic con-tributions are relevant to the interaction (Fig. 3b and supple-mental Fig. 2). The conformation of DD15 and the orientations

TABLE 1Peptides used in the study

TABLE 2FGF-2 binding parameters of peptides and small moleculesBinding constants were obtained by analyzing sensorgrams similar to those shownin Figs. 1c and 4c. Values are the means � S.E. (n, sensorgrams, as indicated). ND,binding not detectable.

n Kon Koff Kd

1/ms 1/s �M

PeptideDD15 6 19.7 � 2.0 5.5 � 0.8 � 10�4 28.0 � 4.0AQ19 ND ND NDDD35 4 10.1 � 0.2 1.2 � 0.2 � 10�4 12.0 � 2.0

Small moleculesm27 (NSC-37204) 4 917.0 � 140.0 3.2 � 0.2 � 10�4 0.3 � 0.1sm8 (NSC-1698) 4 434.0 � 18.0 1.9 � 0.1 � 10�4 0.4 � 0.1sm10 (NSC-636983) 8 15.8 � 1.1 5.2 � 0.6 � 10�4 33.8 � 3.5



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of its side-chain functional groups in themost populated struc-tural cluster from the MD trajectory of the complex were usedas a structural template (Fig. 3c). The distributions of dihedralvalues and distances between critical functionalities were usedto define the upper and lower boundaries for geometric con-straints. Three pharmacophoric points were considered; twonegative ionizable functionalities mapped over the carboxylgroups of Asp-741 and Asp-750 and one five- or six-memberring moiety mapped on the position of the corresponding ringof Pro-748, tomimic the peptide hydrophobic patch defined byI747-P748 and provide structural rigidity to hits (Figs. 2a and3b). The ring moiety was allowed to be either aliphatic or aro-matic and contain carbon, oxygen, nitrogen, or sulfur atoms.The pharmacophore was used to screen the NCI2003 data

base of molecules (containing �300,000 compounds) (Devel-opmental Therapeutics Program, NCI/ National Institutes ofHealth (nci.nih.gov) (44). This search yielded 258 compounds.Subsequent filtering based on bioavailability rules and maxi-mum number of rotatable bonds (RB � 6) reduced the numberof hits to 130 and 42molecules, respectively. Nineteen of them,made available from the NCI, National Institutes of Healthwere subjected to experimental analysis of FGF-2 binding.In preliminary screening, all the molecules were tested at a

high concentration (50 �M) for their ability to compete for thebinding of the labeled type III repeats to FGF-2 (Fig. 4a). Threemolecules (sm8, sm27, and to a lesser extent sm10, Fig. 4b)showed significant competition activity and were tested fur-ther. In a dose-response analysis, sm27 was more potent than

sm8 in preventing the binding of the TSP-1 domain to FGF-2(with IC50 of 1.3 and 8.2 �M respectively; not shown). Analyzedby SPR, both sm27 and sm8 gave significant binding signalsdespite their low molecular weight (Fig. 4c). The sensorgramsindicated submicromolar affinity (Kd �400 nM) with fasterassociation rates and slower dissociation rates than DD15(Table 2). Sm10 showed much lower affinity (Kd 34 �M).Biological, Antiangiogenic Activity of the New Leads in Vitro

and in Vivo—The high affinity interaction of lead molecules withFGF-2 suggested they might retain the antiangiogenic activity ofthe entire TSP-1 and the type III repeats (12, 14). Indeed, bothsm27 and sm8, althoughnot sm10, inhibited the binding of FGF-2to endothelial cells (Fig. 5a). The effectwas dose-dependent, sm27beingmorepotent thansm8(meanIC5024.0�6.9and79.9�28.1�M, respectively). The binding assaymeasures total bound FGF-2,mainlyFGF-2bound toHSPG.The finding, therefore, indicates aninhibitory effect on FGF-2 binding to cell surface HSPG. At thesame concentrations, the two molecules also inhibited FGF-2-in-duced endothelial cell proliferation (Fig. 5b), with only a marginaleffect on proliferation induced by serum (not shown). Again, themost active was sm27 (mean IC50 20.3� 5.9�M) followed by sm8(IC50 67.8� 15.9�M),whereas sm10hadonly amodest inhibitoryeffect. FGF-2-induced proliferation of fibroblasts (NIH-3T3 cells),not inhibited by TSP-1, was also not inhibited by sm27 (notshown). Themost activemolecule, sm27, was tested in vivo in thechorioallantoicmembrane assaywhere angiogenesis is inducedbyFGF-2 embedded in gelatin sponges. Sponges loaded with FGF-2alone induced a macroscopic angiogenic response that was not

FIGURE 2. Structural characterization of the interactions between DD15 and FGF-2. a, shown is a central structure of the most populated cluster from thesimulation of the DD15�FGF-2 complex. The surface of FGF-2 is colored according to the electrostatic potential, with blue corresponding to positive charge density, redto negative charge density, and white hydrophobic surface. The residues highlighted for DD15 are the ones used as templates for pharmacophore design. b, the centralstructure of the most populated cluster from the simulation of the DD15�FGF-2 complex suggests that DD15 and heparin compete for the same binding site.



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observedwith sponges loadedwith FGF-2 and sm27 (Fig. 5c). Thepresence of the smallmolecule (0.5�g) reduced themeannumberof blood vessels entering the sponge from26� 4 (FGF-2 alone) to10 � 2 (FGF-2 � sm27, p � 0.001, n � 10). No inhibition wasobserved with a lower dose of sm27 (0.15 �g) nor with the DD15peptide (not shown), in agreement with the lack of activity of thepeptide in vitro. Interestingly, angiogenesis induced by vascularendothelial growth factor was not affected by sm27 (not shown).These findings confirmthat smallmoleculesmimeticof theFGF-2binding sequence of TSP-1 bind and sequester FGF-2, inhibitingits angiogenic activity.

DISCUSSION

Pathological angiogenesis underlies a wide range of diseases,including cancer, autoimmune diseases, atherosclerosis, andrheumatoid arthritis. Endogenous inhibitors of angiogenesis

are a powerful source of tools for developing therapies for thesediseases. Among them, TSP-1 is an attractive, not yet fullyexploited model for potential new compounds.We report the identification of an FGF-2 binding sequence of

TSP-1 within the type III repeats and the discovery of smallmolecule mimics of this sequence that retain the ability to bindFGF-2 and inhibit angiogenesis. To achieve this goal, we devel-oped amultidisciplinary strategy integratingmolecular and cellbiology, peptide array, computational biology, NMR spectros-copy, and drug discovery to develop amolecular understandingof the TSP-1-FGF-2 interaction and use this information tosearch for small molecule leads. This strategy identified threesmall molecules as possible starting points for the developmentof novel anticancer agents.To locate the FGF-2 binding sequence within the TSP-1 type

III repeats, we used peptide array technology, widely employed

FIGURE 3. a, STD NMR spectra are shown of DD15 peptide in the presence of FGF-2. Upper spectrum, shown is a reference 1H NMR spectrum of 0.7 mM DD15peptide in the presence of 40 �M FGF-2 in 30 mM buffer phosphate (95% D2O, 5% H2O), 50 mM NaCl, and pH 7.0 recorded at 7 °C on a 500 MHz Brukerspectrometer. Lower spectrum, shown is a 1H NMR STD spectrum of DD15 peptide in the same experimental conditions as the reference spectrum (18:1peptide:FGF-2 ratio) with 4.5 s irradiation time in the aromatic region. The assignment of the STD signals is reported, an asterisk marks a signal due to animpurity, and the Ac label indicates the acetyl N-terminal group (see supplemental Methods). b, shown is projection on the central structure of the mostpopulated cluster of DD15 residues (cyan) in contact with FGF-2 residues (blue) is shown. Cyan spheres represent the peptide segment Lys-746-Asp-750,involved in the FGF-2 interaction as determined in STD-NMR experiments showing consistency between the model of the complex from simulations and NMRdata. c, the pharmacophore model projected on the bound conformation of DD15 is shown.



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to map ligand-interacting linear sequences. Our finding of apeculiar pattern of repetitive active peaks is consistent with therepetitive nature of this TSP-1 domain. Of the three potentiallyactive sequences, only DD15 retained the ability to bind FGF-2in experimental binding assays, as confirmed by SPR and NMRanalysis. Interestingly, this sequence is different from otheractive sites mapped in the type III repeats, such as the integrininteracting RGD, binding sequences for cathepsin G, neutro-phil elastase, collagen V, and the attachment sites for neutro-phils and sickle red blood cells (45–48). The type III repeatscomprise 13 aspartate-rich calcium-binding repeats of theN-type or C-type (6, 48). The DD15 sequence is located in thethird, C-type calcium binding wire repeat (supplemental Fig. 3)and is conserved in TSP-2 and cartilage oligomeric matrix pro-tein. Calcium inhibits the binding of TSP-1 and its type IIIrepeats to FGF-2 (12). In a crystal structure that includes calci-um-replete type III repeats of TSP-2 (49), the sequence homol-ogous toDD15 follows a tortuous path that contributes to coor-dination with four calcium atoms through the side chains of

residues homologous to Asp-739,Asp-741, Asp-742, Asp-743,Asn-744, Asp-745, Asp-749, andAsp-752 and the main chain car-bonyls ofAsp-739,Asp-741, and Ile-747 (supplemental Fig. 3). Thus,when the calcium binding sites areoccupied, the sequence would notbe expected to adopt the highly neg-atively charged, extended confor-mation that interacts with FGF-2.However, the cysteine residues thatflank the DD15 sequence are disul-fide-bonded not to one another butto other cysteines, N-terminal orC-terminal. Therefore, the DD15sequence is not constrained by adisulfide and has the potential toextend into the active conformationwhen calcium is removed.The synthetic peptide DD15

bound FGF-2with lower affinity (Kd28 �M) than the whole TSP-1 (Kd 11nM) or the type III repeats (Kd 314nM) (12, 13). The biotin used to labelthe peptides might partly accountfor that. Indeed, an unlabeled DD15peptide had higher affinity forFGF-2 than the biotin-labeled pep-tide (Kd 3.6 and 28 �M, respectively;not shown), indicating a possibleunderestimation of the affinity val-ues calculated with biotin-labeledpeptides. Nonetheless, the progres-sive drop in affinity from the entiremolecule to the fragment and to thesmall peptide suggests a contribu-tion of other residues to FGF-2binding. This is supported by the

increased affinity of larger recombinant domains (see Fig. 1d)or extended synthetic peptides (such asDD35). Adjacent TSP-1regions might contribute to FGF-2 binding by providing con-tacts that cooperatively increase affinity or inducing structuralchanges that favor the exposure and correct conformation ofthe active site. It is well known that the conformation and activ-ity of the type III repeats are particularly sensitive to the influ-ence of other TSP domains (50).Associated with the decreased affinity, the synthetic peptides

had no biological activity in terms of preventing FGF-2 binding tocells or inhibiting endothelial cell proliferation (not shown).Despite this drawback, the experimental demonstration ofDD15�FGF-2bindingprovided important informationon thepos-sible physicochemical determinants of FGF-2 recognition byTSP-1.The computational model of DD15�FGF-2 complex pre-

dicted the binding of DD15 at the heparin-binding site ofFGF-2. This was confirmed by experimental competitionexperiments and is in agreement with our previous observation

FIGURE 4. a, screening small molecules for their ability to prevent the binding of type III repeats to FGF-2 isshown. Labeled type III repeats were incubated with immobilized FGF-2 in the presence of 50 �M concentra-tions of the 19 small molecules selected by the pharmacophoric search of the NCI2003 data base of molecules.Binding is expressed as a percentage of control, mean, and S.E. from three experiments (p � 0.05(*) and p �0.001 (**), ANOVA followed by Dunnett’s post test). b, shown is the chemical structure of the most activemolecules, sm8, sm10, and sm27. c, shown is SPR analysis of the binding of sm8 and sm27 to FGF-2. The figureshows representative sensorgrams obtained by simultaneous injection of two concentrations of the molecules(10 and 3 �M) for 3 min over sensor chip surfaces immobilizing FGF-2. The curves were analyzed by theLangmuir equation, modeling a simple bimolecular interaction, and the corresponding fittings are shown inwhite. Data are expressed as resonance units versus time.



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that intact TSP-1 aswell as a recombinant fragment comprisingthe type III repeats inhibited the binding of FGF-2 to HSPG onthe surface of endothelial cells and in the extracellular matrix(12–14). The biological importance of this interaction in FGF-2bioavailability and activity suggests that DD15mimicsmight bedeveloped as inhibitors of FGF-2 biological functions.This prompted us to search for small molecule mimics of

DD15.We developed pharmacophoremodels based on ensem-bles of conformations obtained from long MD simulations ofthe DD15�FGF-2 complex and validated by NMR measure-ments. The dynamic pharmacophoric approach had alreadybeen used successfully to develop chaperone and aggregationsmall molecule inhibitors from peptide antagonists (25, 26, 36).The inclusion of dynamics in the small molecule discoveryprocess is particularly important in the case of protein-peptideand protein-protein interaction inhibitors. Conformationaladaptation and selection are intimately related to the recogni-tion between flexible and exposed surfaces. Including receptorand ligand flexibility provides a more realistic physical under-standing of the process with respect to the use of static models,allowing the ligand to undergo conformational changes on theprotein surface to find optimal interaction networks.The present computational biology studies provided an

atomic resolutionmodel of theDD15-FGF-2 interaction and itsdynamic properties that were subsequently benchmarkedthrough NMR-STD experiments. Computational and experi-mental data provided a consistent view of the molecular inter-action determinants of DD15�FGF-2 binding, including both

hydrophobic and electrostatic moi-eties. This information was thentranslated into pharmacophoremodels that enabled us to search fornew small molecule inhibitors ofFGF-2 independently of any prede-termined chemical scaffold orstructure, resulting in three newmolecular candidates for futuredevelopment. In contrast to theoriginal TSP-1 sequence, active onlyin the absence of calcium, thesesmall molecules are modeled tomimic the active conformation ofthe sequence and, therefore, areindependent of the presence of cal-cium ions in the environment. Thesmall molecules are characterizedby a symmetric structure, withtwo negatively charged sulfonatedgroups flanking a central aromaticcore, reminiscent of the suramin-like FGF-2-antagonists, which bindto the heparin-binding site of FGF-2(51). Moreover, these moleculesmeet the stereochemical rules,obtained through a totally differentapproach, proposed to developnaphthalene sulfonates as FGFinhibitors (52). The hits discovered

here have much lower molecular weight than suramin, makingthem interesting for pharmacological development.The most active molecules, sm8 and sm27, bound FGF-2

with high affinity (0.3 �M) and retained the ability of the entireTSP-1 (as well as a recombinant fragment containing the typeIII repeats) to inhibit FGF-2 biological activity; that is, bindingto endothelial cells, induction of endothelial cell proliferation invitro, and induction of angiogenesis in vivo in the chorioallan-toic membrane assay. These activities are consistent with theability of the small molecules and of the entire TSP-1 and thetype III repeats to sequester FGF-2, preventing its interactionwith HSPG (12–14). The HSPG-FGF interaction has a funda-mental role in regulating the bioavailability, signaling, andactivity of numerous FGFs. The possibility that TSP-1, peptideDD15, and sm27 target other FGFs besides FGF-2 warrantsfurther investigation.The clinical experience with inhibitors of angiogenesis, pri-

marily targeting vascular endothelial growth factor, has re-vealed important limitations, such as the phenomenon ofacquired, evasive resistance, associated with the production ofdifferent angiogenic factors including FGF-2 (53). The develop-ment of new agents targeting angiogenic factors other than vas-cular endothelial growth factor has, therefore, become a prior-ity. In particular, FGF-2 is emerging as an attractive target fornew antiangiogenic therapies (54). Our study shows that it ispossible to rationally expand the molecular diversity space ofFGF-2 antagonists, with much smaller and chemically “tracta-ble” molecules than the ones known so far. Clearly, the leads

FIGURE 5. Antiangiogenic activity of small molecules mimetic of the FGF-2-binding sequence of TSP-1.a, shown is binding of FGF-2 to endothelial cells. BAEC were incubated with labeled FGF-2 in the presence ofthe small molecule (1–100 �M). The cell-bound FGF-2 is expressed as a percentage of control (in the absence ofsmall molecules). b, shown is endothelial cell proliferation. BAEC were exposed to 5 ng/ml FGF-2 with the smallmolecule (6 –100 �M) and incubated for 3 days. Proliferation is expressed as a percentage of control (in theabsence of small molecules). c, shown is FGF-2-induced angiogenesis in the chorioallantoic membrane assay.FGF-2 (200 ng) was administered in the absence or presence of sm27 (0.5 �g) on day 8. A representative picturetaken 4 days later is shown. Original magnification, 50�.



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identified here cannot yet be considered real drug candidates,but they do offer a solid base for the extension of traditionalmedicinal chemistry efforts to develop non-traditional strate-gies. In view of their structure, it may be possible to furtherderivatize the leads with combinatorial chemistry and improveon their drug-like properties while maintaining the FGF-2 tar-geting properties.

Acknowledgments—We thank R. Longhi (Consiglio Nazionale delleRicerche) and A. Bikfalvi (University of Bordeaux, France) for kindlyproviding reagents.

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1

Non-peptidic thrombospondin-1-mimics as fibroblast growth factor-2 inhibitors:

an integrated strategy for the development of new antiangiogenic compounds

Giorgio Colombo, Barbara Margosio, Laura Ragona, Marco Neves, Silvia Bonifacio, Douglas S

Annis, Matteo Stravalaci, Simona Tomaselli, Raffaella Giavazzi, Marco Rusnati, Marco Presta,

Lucia Zetta, Deane F Mosher, Domenico Ribatti, Marco Gobbi, Giulia Taraboletti

Supplementary Material

2

Supplementary Figure 1.

Effect of heparin on DD15-FGF-2 interaction. The binding of biotin-labeled DD15 to FGF-2 was

tested in the presence of increasing concentrations of heparin. Binding is expressed as the

percentage of control.

3

Supplementary Figure 2.

Summary of DD15/FGF-2 contacts deduced from MD simulations and NMR data. Left panel: list of

residues making contacts for more than 80% of time during the 60 ns of MD simulations. DD15

residues involved in protein interaction, as deduced by STD NMR, are evidenced by a box. Right

panel: graphical representation of the number of contacts per residue based on MD results. A dotted

box highlights the peptide segment showing the highest number of contacts.

4

Supplementary Figure 3

Structure and coordination of the calcium ions (red spheres) of the Tr4 fragment - spanning from

the third EGF like repeat (E3) to the 4th calcium-binding repeats (4C) and comprising both DD15

and AQ19 sequences - extracted from the crystal structure of TSP-2 (1). The location of the DD15

and AQ9 sequences is indicated (arrows).

5

Supplementary Table 1. Salt-Bridge forming pairs between DD15 and FGF2 and persistence time

calculated over the last 30ns of MD simulations.

FGF residue DD15 residue % of time within 3 Å

Arg105 Asp741 65.2

Lys104 Asp740 29.6

Arg105 Asp745 21.4

Arg129 Asp750 13.4

Arg105 Asp742 12.5

Arg7 Asp749 12.3

Lys110 Asp741 11.6

6

Supplementary Table 2. Hydrogen-Bonding forming pairs between DD15 and FGF2 and

persistence time calculated over the last 30ns of MD simulations.

Donor Acceptor % of time

Asp750N Tyr9OH 64.8

Arg105N Asp741OD2 50.9

Asn12ND2 Asp741OD2 49.3

Asn12ND2 Asp741OD1 40.7

Asp749N Tyr9OH 37.4

Arg105N Asp741OD1 31.8

Arg105NE Asp741OD2 29.1

Thr106OG1 Asp740OD2 27.2

Gly14N Lys746O 27.1

Thr106OG1 Asp740OD1 26.8

Ser128OG Asp143OD1 21.3

Arg105NE Asp741OD1 21.2

Arg105NH2 Asp741OD1 21.2

Ser128N Asp143OD2 20.3

7

Supplementary Table 3. Chemical shift assignment of DD15 peptide in water solution, pH 7.0, at 7 °C.

ΗΝ Ηα Ηβ Ηγ Ηδ Others

Ac 2.05

D739 8.47

D745 4.60 2.76-2.67

K746 8.09 4.32 1.79 1.70 1.42 3.02

I747 8.46 4.45 1.91 1.22-0.98 0.88

P748 4.41 2.34-1.95 2.04 3.70-3.95

D749 8.61 4.56 2.74-2.64

D750 8.46 4.60 2.70

R751 8.34 4.26 1.87 1.66 3.22 7.49, 7.34

D752 8.48

NH2 7.67-7.27

8

Supplementary methods

Recombinant human TSP fragments – The vector pAcGP67.coco, in which cloning sites are

flanked by 5�’ DNA encoding a signal sequence and 3�’ DNA encoding a polyhistidine tag, was used

to express the TSP-derived constructs (2). The recombinant domain comprising the third EGF-like

repeat and the whole calcium binding type III repeats (E3Ca) was prepared as described (3). DNA

encoding the third EGF-like repeat and calcium-binding repeats 1, 1-2, 1-3, or 1-4, i.e., residues

648–717 (Tr1), 648–740 (Tr2), 648–753 (Tr3), or 648–776 (Tr4) were generated by PCR

amplification and inserted into the pAcGP67.coco vector as described (4). Virus was produced,

used to infect High-Five insect cells (Invitrogen) and the recombinant proteins were isolated and

characterized as described (4).

Labeling of proteins – FGF-2 and recombinant type III repeats were biotinylated in PBS (pH 7.4)

with biotinamidocaproate-N-hydroxysulfo-succinimide ester (Sigma, St. Louis, MO), molar ratio

13:1. The biotinylated molecules were isolated by chromatography on Micro Bio-Spin columns

(Bio-Rad Lab, Milan, Italy) for the type III repeats, or purified by affinity chromatography on

heparin-Sepharose (GE Healthcare Biosciences, Uppsala, Sweden) for FGF-2, as previously

described (3,5). Gelatin was added at a final concentration of 0.05%.

Alternatively, FGF-2 was labeled with the lanthanide Europium. Recombinant human FGF-2 (100

µg) bound to heparin-Sepharose in carbonate buffer pH 9.3 (final volume 250 µl) was added to the

lyophilized Europium-labeling reagent (Perkin-Elmer, Wallac Oy, Turku, Finland). After overnight

incubation at 4°C, FGF-2 was eluted from the Heparin-Sepharose resin with TBS 2M NaCl. BSA,

highly purified from heavy metal contaminants (Perkin-Elmer), was added at a final concentration

of 0.1%.

Both biotin- and Europium-labeled FGF-2 run as a band with the expected molecular weight in

15% SDS-PAGE (western blot analysis) and were biologically active, as they bound endothelial

cells and stimulate their proliferation at the same extent as unlabeled FGF-2.

Binding of biotin-labeled peptides or recombinant domain to immobilized FGF-2 – Microtiter

plates (ProBind, Falcon, Becton-Dickinson, Lincoln Park, NJ) were coated overnight at 4°C with

FGF-2 (0.1 µg in 40 µl /well PBS). Plates were washed with PBS 0.1% BSA and non-specific

binding sites were saturated by a 30 minute incubation with PBS 1% BSA. Biotin-labeled peptides

or recombinant domain were added in 40 µl PBS 1% BSA with or without inhibitor, and incubated

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for 3h at room temperature. The plates were washed with PBS 0.1% BSA and treated for 30

minutes with 75 µl/well mouse anti-biotin antibody 1:200 in PBS (Vector Laboratories,

Burlingame, CA) at room temperature. Bound antibody was quantified using the Mouse IgG Elite

Vectastain ABC kit (Vector Laboratories) according to manufacturer’s instructions followed by 1,2-

phenylenediamine dihydrocloride (OPD, Dako, Glostrup, Denmark) as a chromogen. The reaction

was stopped with 0.5M H2SO4 and absorbance was read at 490 nm.

Binding of biotin-labeled FGF-2 to immobilized recombinant domains – Binding was conducted

as described (3). Briefly, microtiter plates were incubated overnight at 4°C with recombinant

domains in 40 µl PBS. The plates were washed with PBS 0.1% BSA and non-specific binding sites

were saturated with PBS 1% BSA. Biotin-labeled FGF-2 (3 ng/40 µl per well) was added in PBS

1% BSA and incubated for 3h at room temperature. Wells were washed and binding quantified as

described (3).

Surface Plasmon Resonance - SPR studies were carried out using the ProteOn XPR36 Protein

Interaction Array system (Bio-Rad) (6). FGF-2 was covalently immobilized onto two parallel flow

cell surfaces of the same Proteon GLC sensor chip (Bio-Rad), using amine coupling chemistry.

Briefly, the surfaces were activated for 5 min with a mixture of EDC (0.2 M) and sulfo-NHS (0.05

M), and this was followed by injection of FGF-2 (40 ug/ml in phosphate buffered saline, pH 7.4),

which flowed for 5 min at a rate of 30 µl/min. The remaining activated groups were blocked with a

5-min injection of 1 M ethanolamine. The amounts of FGF-2 covalently immobilized onto the

surface, expressed in Resonance Units (RU, 1 RU = 1 pg protein/mm2), were about 3500 and 4000

RU in the two flow cell surfaces. A reference channel was always prepared in parallel by the using

the same activation/deactivation procedure but injecting vehicle only.

After the immobilization procedure, the fluidic system of ProteOn is rotated by 90° allowing to test

in parallel up to six different analytes, or up to six different concentrations of the same analyte, over

the target surfaces. Peptides and small molecules were injected over immobilized FGF-2 at a rate of

30 µl/min, for 3 min (association phase), while dissociation was measured in the following 10-15

min. Vehicle was always injected in parallel flow channels. When needed, complete dissociation of

bound analytes was induced by a 30 s injection with 1M NaCl (regeneration step). The running

buffer, also used to dilute analytes, was phosphate buffered saline, pH 7.4, 0.005% Tween 20

(PBST, Biorad). All these assays were done at 25 °C.

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The sensorgrams (time course of the SPR signal in RU) were normalized to a baseline value of 0.

The signal observed in the surfaces immobilizing FGF-2 was corrected at first by subtracting the

non-specific response observed in the reference surface. The signal measured after injection of

vehicle alone allowed to correct for binding independent responses (e.g. drift effects). The resulting

sensorgrams were fitted by the simplest 1:1 interaction model (Langmuir model, ProteOn analysis

software), to obtain the corresponding association and dissociation rate constants (Kon and Koff).

Simulation setup, conformational search and docking experiments – Simulations for DD15 were

started from a fully extended conformation of the peptide. The initial 3D structure was built using

fragments from the standard libraries of MAESTRO v.5.1.016 (Schrödinger). An initial

representative conformation for the peptide was obtained by conformational search using the

Systematic Unbounded Multiple Minimum (SUMM) routine implemented in MACROMODEL v.

8.1 with the AMBER force field and the Polak-Ribiere Conjugate Gradient (PRCG) minimization

method, with a maximum of 700 minimization steps and an energy convergence criterion of 0.05

kJ/mol. The Generalized Born/Surface Area (GB/SA) continuum solvation model was used to

mimic water effects, with a dielectric constant ε of 78. Extended cutoff distances were used for the

treatment of nonbonded interactions (Van der Waals – 8 Å, electrostatic – 20 Å, hydrogen bond – 4

Å). SUMM performed torsional sampling until 30000 conformations were generated. These were

saved if within a 50 kJ/mol energy window from the global minimum. Similar structures were

excluded based on heavy atom superimposition. The global minimum conformation was then

subjected to 60ns of Molecular Dynamics (MD) refinement in explicit water solvent using the same

protocol as described in the next paragraph for MD simulations of the complexes. The resulting

trajectories were analyzed by the structural clustering method described by Daura and coworkers

(7): count the number of neighbors using a cut-off of 0.15 nm rmsd between the optimal backbone

superimposition of different structures, and take the structure with the largest number of neighbors

with all its neighbors as cluster and eliminate it from the pool of clusters. This procedure is repeated

for the remaining structures in the pool.

The representative structure of the most populated cluster of peptide DD15 isolated in solution was

then used for docking analysis with FGF-2. The structure was subjected to blind docking

experiments on the whole FGF-2 receptor using the program AutoDock v. 3.0. The crystal structure

of the protein was taken from the protein data bank (pdb code: 1fq9). The original X-ray structure

contains a dimeric 2:2:2 FGF-2:FGFR:heparin ternary complex which was processed in order

isolate the FGF-2 protein. Mass-centered grid maps were generated with 0.25Å spacing by the

11

program AutoGrid for the whole FGF protein target. Default Lennard-Jones parameters 12-10 and

12-6 were used for modelling hydrogen bonding and Van der Waals interactions, respectively. The

distance dependent dielectric permittivity of Mehler and Solmajer7 was used for the calculation of

the grid map. The Lamarckian genetic algorithm (LGA) and the pseudo-Solis and West methods

were applied for minimization using default parameters. The number of generations was set to 25

millions in all runs, and the stopping criterion was therefore defined by the total number of energy

calculations. Random starting positions on the entire protein surface, random orientations, and

torsions were used for the DD15. 350 different runs were performed with the parameters described

above. Conformational and energetic clustering of the blind docking results (8) yielded a dominant

structural family, whose representative conformation was subsequently used for all-atom MD based

refinement.

Molecular dynamics (MD) - The structures of DD15 docked with FGF-2 were studied in solution

by long time scale molecular dynamics (MD) simulations in explicit water solvent. The complex

was first solvated with water in a periodic truncated octahedron, large enough to contain the

complexes and 0.8 nm of solvent on all sides. The protonation and charge states of the side chains

of the peptides and the receptor were chosen to be consistent with the solution conditions of the

experiments: amine groups were considered as having a +1 charge and carboxylic groups were

considered as having a –1 charge. The FGF/DD15 system was found to have a total charge of +4

(FGF +11 / DDD –7). Four Cl– counter ions were added to the system to ensure electroneutrality.

The system was initially energy minimized with a steepest descent method for 5000 steps. The

temperature was maintained close to the intended value of 300 K by weak coupling to an external

temperature bath, with a coupling constant of 0.1 ps. The DD15/FGF-2 complex and the rest of the

system were coupled separately to the temperature bath. The GROMOS96 force field and the

simple point charge (SPC) water model were used. The LINCS algorithm was applied to constrain

all the bond lengths. For the water molecules, the SETTLE algorithm was used. A dielectric

permittivity, ε =1, and a time step of 2 fs were used. A cut-off of 0.9 nm was used for the

calculation of the non-bonded Van der Waals interactions. The calculation of electrostatic forces

utilized the PME implementation of the Ewald summation method. The molecular dynamics runs

using NVT conditions were 60 ns long. All the MD runs and the analysis of the trajectories were

performed using the GROMACS software package. Configurations of the receptor-ligand complex

were saved every 4 ps for subsequent statistical analysis.

Conformational cluster analysis of the two trajectories was performed using the method described

by (7).

12

The results of the conformational analysis were benchmarked against NMR-STD data. Statistical

analysis of contacts, hydrogen bonds, hydrophobic and electrostatic interactions was carried out

and the statistically most relevant interactions were used as a template for pharmacophore design,

according to the procedures described in (9,10). A three-point model was created by assembling

two negative ionisable groups mapped over the two Asp741 and Asp750 carboxy groups, and one

five or six membered ring moiety mapped over the Pro748 ring of the representative DD15

conformation bound to FGF-2.

Electrostatic surface potential calculation - Electrostatic potentials were calculated in an aqueous

solution with dielectric constant ε = 78.54, by solving the full non-linearized form of the Poisson

Boltzmann equation with the Adaptive Poisson-Boltzmann Solver (APBS) v. 0.4.0. A dielectric

constant ε = 2 was employed to the protein. The potential was represented at the solvent accessible

surface using a probe of 1.4 Å radius (water molecule).

Nuclear Magnetic Resonance (NMR) spectroscopy - DD15 peptide was dissolved at 0.7 mM

peptide concentration in 30 mM water phosphate buffer, 50 mM NaCl, pH 7 and analysed by 1H 1D

and 2D NMR techniques at 7°C. For DD15/FGF-2 interaction studies samples of 40 µM FGF-2 in

the presence of 0.7 mM peptides in 30 mM deuterated buffer phosphate (95% D2O, 5% H2O),

50mM NaCl and pH 7.0 were prepared and analyzed by Saturation Transfer Difference (STD)

NMR techniques at 7 °C.

NMR spectra were recorded on a Bruker DMX 500 MHz NMR spectrometer equipped with a triple

resonance probehead, incorporating gradients in the z-axis. All data were collected on a spectral

width of 6510 Hz. TOCSY, ROESY and NOESY spectra were recorded using standard sequences

(11,12). A spin lock time of 80 ms was used for TOCSY, mixing times of 150 ms were used for

ROESY and NOESY spectra. Longitudinal relaxation times T1 of the peptide resonances were

measured in the presence of FGF-2 protein with the standard inversion recovery method. Data

points (32 K) were acquired to cover a sweep width of 6510 Hz and a relaxation delay of 8.5 s was

used. Data were analysed using Bruker Topspin software. T1 values were found to be rather

constant along the peptide side-chains in a range of 0.5-0.8 s, except for a longer T1 value measured

for methyl protons of acetylic group (1.3 s).

For the acquisition of STD NMR experiments a 1D pulse sequence incorporating a T1ρ filter to

remove disturbing protein signals was used (13). On-resonance irradiations were performed at

different frequencies in the methyl (-236 Hz) and aromatic (3220 Hz) regions and off resonance

irradiation was performed at –15000 Hz, using a series of Gaussian pulses with a 1% truncation and

13

50 ms duration to give different total saturation times of 2, 2.5, 3, 4, 4.5 s. The selective saturation

of the protein was checked by collecting a STD control spectrum in the same experimental

conditions on the ligand alone which did not show any signal, thus excluding direct excitation of the

peptide resonances. The duration of the T1ρ filter was 30 ms. STD NMR spectra of 32 K data points

were acquired with a total of 128 transients in addition to 32 scans to allow the sample to come to

equilibrium. STD spectrum was obtained by subtraction, through phase cycling, of saturated fid

from the reference one, obtained with off resonance irradiation. In the STD spectra a singlet at the

frequency of N-terminal acetylic group is visible. The contribution of this group to the protein

contact interface could not be properly evaluated due to relaxation properties of these protons

(longer T1 value with respect to the rest of the peptide side-chain protons) which could enhance

STD signal intensity (14).

Pharmacophore generation - A pharmacophoric hypothesis was built (HYP-DD15) based on the

results of the MD simulations. The conformation of DD15 and the orientations of its side-chain

functional groups in the most populated structural cluster from MD trajectories of the complex were

used as structural template. The HipoGen module of the Catalyst from Accelrys was used for this

purpose. Furthermore, we imposed location constraints (the volume in which the functions can

reside), specifying a 1.6 Å tolerance as the radius of the spheres. This hypothesis was used as query

for a search in the NCI2003 3D database using the database search module of Catalyst. Post-

filtering of the retrieved hitlist was performed using Instant JChem v. 2.0. Compounds expected to

have reduced bioavailabity were excluded based on calculated molecular descriptors consistent with

a drug-like character of the selected molecules (molecular weight ≤ 500, logP ≤ 5, hydrogen bond

donors ≤ 5, hydrogen bond acceptors ≤ 10, polar surface area ≤ 200, fused aromatic rings ≤ 5).

Compounds with at least 5 of these features were accepted. Finally, extended molecules with a large

number of rotatable bonds were excluded (rotatable bonds ≤ 6).

Binding of FGF-2 to endothelial cells - Subconfluent cultures of bovine aortic endothelial cells

(BAEC) in 96-well plates were incubated for 30 min at 4 °C in serum-free DMEM with 0.15%

gelatin and 25mM HEPES (DMEM-gelatin). The medium was then replaced with cold DMEM-

gelatin containing Eu-labeled FGF-2 (final concentration 10 ng/ml) with or without the indicated

concentrations of small molecules. The plate was incubated for 2 h at 4 °C, washed with cold

DMEM-gelatin to remove unbound FGF-2. To measure the amount of bound FGF-2, 100 µl

DELFIA Enhancement Solution (PerkinElmer) were added and incubated for 10 minutes on a

14

plate shaker. Time resolved fluorescence was then measured using a Victor3 multilabel plate reader

(PerkinElmer).

Endothelial cell proliferation assay - Bovine aortic endothelial cells (BAEC, 2500 cells/well) were

plated in 96-well plates in DMEM 1.5% FCS. After 24 h, the medium was substituted with DMEM

0.5% FCS, with or without FGF-2 (5 ng/ml) and the indicated concentration of small molecules,

and incubated for 72 h. Plates were then stained and analyzed as described (15).

Chorioallantoic membrane (CAM) assay - Fertilized White Leghorn chicken eggs were incubated

at 37°C at constant humidity. On day 3, a square window was opened in the shell, 2–3 ml of

albumen was removed to allow detachment of the developing CAM, and the window was sealed

with a glass. On day 8, 1 mm3 sterilized gelatin sponges (Gelfoam Upjohn, Kalamazoo, MI) were

placed on the CAM as described (16). Sponges were loaded with: 1 l of PBS or FGF-2 (200 ng),

with or without sm27 (0.5 µg). At day 12, CAMs were photographed in ovo under a

stereomicroscope (Olympus), and blood vessels entering the sponge within the focal plane of the

CAM were counted by two observers in a double blind fashion.

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