Biomimetic Design of Platelet Adhesion Inhibitors to Block Integrin

Apr 3, 2014 - Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, People,s Republic of China. •S Supporti...
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Biomimetic Design of Platelet Adhesion Inhibitors to Block Integrin α2β1-Collagen Interactions: II. Inhibitor Library, Screening, and Experimental Validation Lin Zhang,†,‡ Chao Zhang,†,‡ and Yan Sun*,†,‡ †

Department of Biochemical Engineering and Key Laboratory of Systems Bioengineering of the Ministry of Education, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, People’s Republic of China ‡ Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, People’s Republic of China S Supporting Information *

ABSTRACT: Platelet adhesion on collagen mediated by integrin α2β1 has been proven important in arterial thrombus formation, leading to an exigent demand on development of potent inhibitors for the integrin α2β1-collagen binding. In the present study, a biomimetic design strategy of platelet adhesion inhibitors was established, based on the affinity binding model of integrin proposed in part I. First, a heptapeptide library containing 8000 candidates was designed to functionally mimic the binding motif of integrin α2β1. Then, each heptapeptide in the library was docked onto a collagen molecule for the assessment of its affinity, followed by a screening based on its structure similarity to the original structure in the affinity binding model. Eight candidates were then selected for further screening by molecular dynamics (MD) simulations. Thereafter, three candidates chosen from MD simulations were separately added into the physiological saline containing separated integrin and collagen, to check their abilities for blocking the integrin−collagen interaction using MD simulations. Of these three candidates, significant inhibition was observed in the presence of LWWNSYY. Finally, the binding affinity of LWWNSYY for collagen was demonstrated by isothermal titration calorimetry. Moreover, significant inhibition of platelet adhesion in the presence of LWWNSYY has been experimentally validated. This work has thus developed an effective strategy for the biomimetic design of peptide-based platelet adhesion inhibitors.

1. INTRODUCTION

In the present study, a biomimetic design strategy of platelet adhesion inhibitors was proposed to develop potent highaffinity inhibitors on the integrin α2β1-collagen binding, as a combination of molecular docking,18−24 structure similarity analysis, MD simulations,25−32 and experimental validation. There are two parts in this work. In part I, the authors have constructed an affinity binding model (ABM) of integrin to mimic the integrin binding on collagen surface. In part II, the efforts have been focused on the library design and screening of inhibitors based on the ABM. First, a heptapeptide library was designed. Then, molecular docking was employed to screen heptapeptides with sufficient affinity to the collagen. The structure similarity of each candidate to its original structure in the ABM was evaluated using root-mean-square deviation (RMSD), which was used as criteria for mimicking the binding motif of integrin. Thereafter, MD simulations were performed to determine the binding dynamics. The candidates with both high binding probabilities and proper binding sites were considered as potential high-efficiency inhibitors, which were

Platelet adhesion on collagen mediated by integrin α2β1 has been proven important in arterial thrombus formation,1−6 leading to an exigent demand on the development of potent inhibitors on the integrin α2β1-collagen binding. Structurebased rational design in combination with virtual highthroughput screening7−9 is a fast method to identify novel inhibitors from a large library of candidates within a relatively short period of time. It is advantageous in its low cost of time, labor, and materials with numerous successful applications in drug discovery and design of affinity ligands.10−17 Therefore, many efforts have been devoted to the rational design of high affinity ligands for integrin. For instance, Munoz et al.10 used computer-aided macromolecular interaction assessment to select anti-thrombotic molecules that mimic and therefore block platelet GPIb binding to von Willebrand factor (VWF). Broos et al.17 identified a small molecule that modulates platelet GPIbα-VWF interaction by molecular dynamics (MD) simulations and molecular docking. Heckmann et al.12,13 described the rational design and synthesis of ligands for integrin receptors α5β1 and αvβ3, and then optimized the selectivity by means of extensive SAR studies and docking. © 2014 American Chemical Society

Received: November 29, 2013 Revised: March 22, 2014 Published: April 3, 2014 4734

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Scheme 1. Biomimetic Design and Screening of Platelet Adhesion inhibitors

interface energy score (I_sc) was used for evaluating the binding affinity of candidate on the collagen. 2.4. Binding Dynamics of the Peptides on Collagen. The binding abilities of selected ligand candidates were then examined using MD simulations. The simulation system was prepared as part I with minor modification. A candidate and a collagen were first placed in the center of a cubic box (10 × 7 × 5.5 nm3). Then, solvent molecules were added randomly, followed by the neutralization of system by adding Na+ as counterions; where the TIP3P model was used for water molecule, Na+ and Cl− were considered as charged beads. The parameters for hydroxyproline were taken from the literature.41 Thereafter, MD simulations in the NVT ensemble were performed by GROMACS with CHARMM27 force field. Temperature was controlled at 298.15 K by the velocity-rescale (v-rescale) method42 with a time constant of 0.5 ps. Linear Constraint Solver (LINCS) algorithm43 was applied to constrain all bonds. Periodic boundary was used in x, y, and z directions. Particle-mesh Ewald (PME) algorithm44,45 was used to deal with the electrostatic interaction. The cutoffs of neighbor atom list, Lennard-Jones (LJ) potential, and Coulomb potential energies were all set to 0.9 nm. The initial velocities of particles were generated according to a Maxwell distribution. Verlet algorithm was used for integration with a time step of 2 fs. An energy minimization was performed, followed by 10 ns MD simulation. Eight independent simulations were performed for each candidate. The potential energies between candidate and collagen, including LJ and Coulomb potential energies, were calculated using g_energy program in GROMACS. The total binding energy, denoted as EMD, was calculated as the sum of LJ and Coulomb potential energies to evaluate the molecular interactions. The binding probability, denoted by Pbind, was defined and calculated as the percentage of duration time of binding state in the last 1 ns of simulation. Pbind was used for evaluating the binding ability of each ligand candidate. 2.5. Verification on the Ability of Inhibiting IntegrinCollagen Binding. The simulation system of separated integrin and collagen was prepared as part I. That is, the proteins (separated integrin and collagen) were first placed in the center of a cubic box (10 × 7 × 9.5 nm3). Then, five candidate molecules with random orientations and locations were added into the simulation box around the integrin and collagen. Thereafter, solvent molecules were added randomly, followed by the neutralization of system by adding Na+ as counterions. After energy minimization, 50 ns MD simulation was performed. All the parameters were the same as those in Section 2.4. The minimum distance between the candidates and collagen (denoted as dmin) was calculated using g_mindist program in GROMACS to describe the binding/dissociation. The potential energies and the binding probability were calculated as described in Section 2.4, but the last 5 ns simulation was used for the calculation of Pbind. 2.6. Circular Dichroism Spectroscopy. The triple helical collagen peptide, with an amino acid sequence of (GPO)2GFOGER(GPO)3, was purchased as HPLC-purified powder with a purity of >95% from ChinaPeptides (Shanghai, China). Circular dichroism (CD) spectra from 260 to 190 nm were collected at 10 °C using a Jasco 810 spectrophotometer (Jasco Inc., Tokyo, Japan). Samples were prepared at a concentration of 0.3 mg/mL in ethylene glycol (EG/

then added into a physiological saline containing separated integrin and collagen to verify their abilities of inhibiting the integrin-collagen binding by MD simulations. Finally, the binding affinity of candidates for collagen was demonstrated by isothermal titration calorimetry (ITC). The inhibition of platelet adhesion in the presence of potential inhibitor was examined for further experimental validation.

2. MODELS AND METHODS 2.1. Design of Peptide Library. A heptapeptide library of LXXNSXY was rationally designed based on the ABM proposed in part I, where X was an arbitrary amino acid residue, as illustrated in Scheme 1. The three-dimensional structures of peptides were determined and optimized using CHARMM33 program (http:// www.charmm-gui.org/). 2.2. Docking of the Peptides to Collagen. Crystal structure of collagen with triple helical structure in Protein Data Bank (PDB ID: 1DZI, http://www.rcsb.org/pdb/)34 was used as the receptor for docking, while the candidate in the designed peptide library was used as the ligand. Both the receptor and ligand were prepared using AUTODOCKTOOLS 1.5.6.35 In the receptor, all polar hydrogens were added and Kollman United Atomic Charges were computed. In the ligand, the Gasteiger charges were computed. Grid definition was set up following the recommendations of the program manual.35 The structures of the receptor and ligand were then saved in pqbqt format. Thereafter, the ligand was docked to collagen using AUTODOCK VINA 1.1.236 (http://vina.scripps.edu/)hereafter termed VINA. The affinity energy value (kcal/mol) for each ligand was calculated and denoted by EVINA. EVINA is not equal to the potential energy or binding free energy, but an empirically weighted scoring function for the evaluation of binding affinity. Then EVINA of each candidate was compared for the screening. For each ligand candidate, the best docked conformation was chosen for the following analysis. 2.3. Structure Similarity Analysis of the Peptides. For each selected candidate by VINA, its structure similarity to the original structure in the ABM was evaluated using RMSD. RMSD representing the structural deviation of a candidate with respect to a reference structure (herein the structure in the ABM was used) was calculated using g_rms program in GROMACS 4.5.3 package37,38 (http://www. gromacs.org/). Each candidate LXXNSXY contains four key residues, L, N, S, and Y from the ABM. The conformation of these four residues may be changed during the docking. Then RMSD of these residues was calculated with respect to the original structure in the ABM to provide a quantitative evaluation of the change. Small RMSD indicates a similar binding structure of this candidate as that in the ABM. Furthermore, the binding sites of each candidate were checked according to the ABM, and the candidate without similar binding sites was not considered in the following screening. Thereafter, Rosetta FlexPepDock39 was utilized to verify the candidates selected by VINA and structure similarity analysis. Rosetta FlexPepDock is a high-resolution peptide docking (refinement) protocol, which incorporates full flexibility for peptides as well as side chain flexibility for receptor proteins.40 In the present study, 200 optimization models were produced for each candidate. Then, the 4735

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H2O, v/v, 1:3) or deionized water, and then injected into a 1 mm path length quartz cuvette. All solutions were equilibrated at 4 °C for at least 12 h prior to recording spectra. A background CD spectrum of buffer solution was subtracted from the sample spectra for baseline correction. Spectra were recorded using a resolution of 0.5 nm and a scanning speed of 100 nm/min, with a response time of 1 s and a bandwidth of 2 nm. The presented spectrum was an average of three consecutive measurements. The spectra were analyzed by Jascow32 provided by the manufacturer. 2.7. Isothermal Titration Calorimetry. LWWNSYY was obtained as lyophilized powder with a purity of >95% from GL Biochem (Shanghai, China). In the examination of binding, the concentration of collagen peptide in the cell was 1.2 mM, while the concentration of LWWNSYY was 100 μM. The collagen peptide solution was treated by 20 min degassing prior to the examination. Isothermal calorimetric titrations were performed in a titration mode with a 1.425 mL sample cell, using a VP isothermal titration calorimeter (MicroCal, Northampton, MA). An 8 μL LWWNSYY solution was injected over 16 s for 30 times, with a spacing time of 500 s between injections. The reference power was set to 20 μcal/s, and the stirring speed was 307 rpm. To reserve the active triple helical form of collagen peptide, the temperature in ITC cell was kept at 10 °C. In control, the titrant was injected into the buffer in the sample cell to obtain the heat of dilution, which was subtracted in following analysis. Titration data were analyzed using MicroCal Origin (version 7.0). All possible binding sites were assumed to have the same binding energy. Consequently, the integrated enthalpy was calculated from the single-site binding model. Thermodynamics parameters, including Kd, ΔH, TΔS, and Gibbs free energy (ΔG) were calculated. 2.8. Measurement of Platelet Adhesion. Sheep blood containing 0.4% sodium citrate (w/v) was purchased from Ruite Biotec (Guangzhou, China). Platelet-rich plasma (PRP) was prepared from sodium citrate anticoagulated blood by centrifugation of 20 min at 180 g. Thereafter, centrifugation of 10 min at 1000 g was performed on PRP to prepare platelet-poor plasma (PPP), while centrifugation of 5 min at 4 °C and 6000 g was performed on PRP to prepare plateletfree plasma (PFP). Collagen peptide with a concentration of 0.2 mM was prepared in PBS, where 1 L PBS contains 80 g NaCl, 2.0 g KCl, 14.4 g Na2HPO4, 2.4 g KH2PO4, and 1.9 g MgCl2 (pH 7.4).46 900 μL PRP was preincubated at 22 °C for 5 min. Then 100 μL collagen peptide was added to induce platelet adhesion, which was measured turbidimetrically by Rayleigh UV-1801 ultraviolet spectrophotometer (Beijing, China) at 22 °C after a time interval of 25 min. The decline of optical density at 600 nm was used for evaluating the platelet adhesion because a positive correlation exists between the number of platelets and the optical density.47 100 μL PBS was added into 900 μL PRP, which was used as a control. To evaluate the inhibition of platelet adhesion by LWWNSYY, collagen peptide was incubated together with LWWNSYY (hereafter termed blocked collagen) at 4 °C for 12 h, where the molecular ratio of collagen/LWWNSYY was set to 1:1.5. Then 100 μL blocked collagen was added into 900 μL PRP, subject to the measurement of optical density. Meanwhile, 100 μL LWWNSYY (0.3 mM) was added into 900 μL PRP and used as control. Four independent assays were performed and the average was used for discussion.

Table 1. Binding Free Energies (kcal/mol) of Each Residue in the Affinity Binding Model residue L220 N154 S155 Y157 R288 a

ΔGnonpolar −2.0 −3.5 −1.1 −4.6 −0.3

± ± ± ± ±

0.3 0.8 0.6 0.8 0.3

ΔGpolar 0.1 −0.8 −2.4 −0.5 −2.9

± ± ± ± ±

0.4 1.2 2.5 1.0 3.3

ΔGbinda −1.9 −4.2 −3.4 −5.1 −3.2

± ± ± ± ±

0.6 1.0 2.3 0.8 3.3

ΔGbind = ΔGnonpolar + ΔGpolar.

R288 only accounts for 18%. Then R288 is not considered in the design of peptide library. According to the distances, two residues are inserted between L220 and N154, while one is inserted between S155 and Y157, leading to a heptapeptide library of LXXNSXY, where X is an arbitrary amino acid residue. Then, 8000 candidates are included in the peptide library, as illustrated in Scheme 1. 3.2. Docking of the Peptides to Collagen. The binding ability of each peptide candidate in the library was then determined by molecular docking to the target collagen. The ranking of each candidate was evaluated by EVINA, as shown in Table S1 and Figure S1a. It can be seen that EVINA of the ligand candidates ranges from −3.7 to −7.2 kcal/mol, indicating widespread candidates in the library. Then, based on the distribution of EVINA (Figure S1a), 177 peptide candidates with EVINA ≤ −6.5 kcal/mol are selected subject to following screening. 3.3. Structure Similarity Analysis of the Peptides. The ABM proposed in part I is the basis of peptide library design. Then for each candidate, high structural similarity of docked conformation to the original structure in the ABM should be obtained to mimic the binding behavior in integrin−collagen complex. Therefore, the structural similarity has been evaluated by RMSD, where the original structure in the ABM is chosen as the reference structure. The distribution of RMSD is shown in Figure S1b. For the 177 candidates selected by EVINA, RMSD ranges from 0.26 to 0.6 nm, indicating effective screening using RMSD. Based on the distribution of RMSD (Figure S1b), 25 candidates with RMSD ≤ 0.4 nm are selected, as shown in Scheme 1. Furthermore, the binding sites of these candidates were compared to the ABM. Among them, only eight candidates have similar binding sites, as shown in Figure 1, where the docked conformation is shown in red and the original structure in the ABM is shown in blue. EVINA and RMSD of the eight candidates are summarized in Table 2. Good superposition of N4, S5, and Y7 is observed by all eight candidates (Figure 1), indicating their binding abilities on collagen surface. The superposition is dependent on the location of individual residue. Three residues with good superposition are all located in the groove of the triple helical structure of collagen, leading to more stable binding than other residues. In contrast, L1 is an important residue located on the ridge, which is flexible and has never been well covered by the eight candidates. Then the similarity between the docked conformation of selected candidate and the original structure in the ABM is not very satisfied. Rosetta FlexPepDock was then utilized to verify the candidates in consideration of the flexibilities of both the candidates and collagen, as shown in Table S2. For the 25 candidates selected by VINA and structure similarity analysis, a range of I_sc from −23.4 to −16.1 is observed, where all eight candidates with proper binding sites have low I_sc values. For example, three of the eight candidates

3. RESULTS AND DISCUSSION 3.1. Design of Peptide Library. There are five residues in the ABM proposed in part I (Scheme 1), including L220, N154, S155, Y157, and R288, whose contributions to the binding free energy are listed in Table 1. All five residues in the ABM can be used for library design. However, the distances between these residues (Scheme 1) indicate that R228 is far from the first four residues. Including R228 in the library design causes a huge number of candidates up to 64 million, which is impossible for the screening. Moreover, from Table 1 it can be seen that the first four residues account for 82% of the total binding free energy while 4736

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Figure 1. The superposition of the docked conformation of selected candidate to the original structure in the affinity binding model. Eight selected ligand candidates are shown, where a lateral view is shown on the right. Collagen is shown in gray as a ribbon structure, the docked conformation of candidate is shown in red as a sticks model, and the original structure in affinity binding model is shown in blue as a sticks model. The figures are prepared using RASMOL program (http://www.umass.edu/microbio/rasmol/).

Table 2. Eight Peptides Selected by RMSD and Binding Site Comparison

a

candidate

EVINA (kcal/mol)

RMSD (nm)

I_sc

LAFNSWY LFDNSRY LRWNSPYa LWWNSNY LWWNSPY LWWNSYYa LWYNSGY LYWNSGYa

−6.5 −6.5 −6.6 −6.7 −7.0 −6.6 −6.7 −6.5

0.33 0.38 0.29 0.39 0.37 0.36 0.39 0.39

−19.0 −20.1 −20.6 −18.4 −17.8 −23.4 −18.0 −21.4

EMD (kJ/mol) −98 −51 −158 −79 −73 −85 −74 −142

± ± ± ± ± ± ± ±

66 72 106 64 58 60 69 74

Pbind 0.76 0.50 0.89 0.75 0.76 0.87 0.75 1.00

± ± ± ± ± ± ± ±

0.45 0.53 0.33 0.46 0.42 0.35 0.45 0.00

The three peptides were considered as potential inhibitors.

Figure 2. Binding dynamics of the three selected ligand candidates on collagen surface. Collagen is shown in gray as a ribbon structure and the ligand in red as a sticks model.

3.4. Binding Dynamics of the Peptides on Collagen. Further screening of each candidate was performed by MD simulations to check its binding ability on collagen surface in physiological saline. Their binding sites on collagen surface were also examined. The binding energy (EMD) and the binding probability (Pbind) of each candidate are summarized in Table 2.

selected by binding site comparison, LWWNSYY, LYWNSGY, and LRWNSPY, are in the top five of the best docking by FlexPepDock (Table S2), indicating effective and suitable screening using the binding site comparison. The I_sc values of eight selected candidates are provided in Table 2. 4737

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Negative EMD is observed for all the eight candidates, leading to the binding on collagen surface with a Pbind ranging from 0.50 to 1.00. LRWNSPY and LYWNSGY have high Pbind as well as low EMD. Meanwhile, LWWNSYY has an EMD of −85 kJ/ mol, which is fourth in the eight ligands, but has a third high Pbind of 0.87. So, these three candidates are considered as potential inhibitors. Their binding dynamics are described by snapshots in Figure 2. All three candidates can bind on collagen surfaces with similar binding sites as the ABM (Figure 2), but vary in the binding velocities. LRWNSPY approaches the collagen slowly (ca. at 2 ns), and finally achieves similar binding as the ABM at 10 ns. A different style is observed in the binding of LWWNSYY. The C-terminal, mainly the two tyrosine residues, come into contact with the collagen at 1 ns, mediating the following binding. The binding through the C-terminal remains for a long time (ca. at 2 ns), leading to the weak binding energy (Table 2). However, binding with multiple contacts is formed finally at 10 ns. For LYWNSGY, fast binding is observed at 1 ns, but a little far from the expected binding site. In the following simulation, conformational transition of the ligand is observed as well as the movement along the collagen, leading to the final binding similar to the ABM. In Figure 3, the binding conformation in MD simulations (green) is compared to the docked conformation (red), as well

evidence of inhibition. Herein, the molecular ratio of inhibitors to integrin/collagen was set to 5:1. There is no standard value of molecular ratio according to the literature.48,49 Various values of molecular ratio have been examined and the ratio of 5:1 is proven suitable for the simulations in the present study. The dynamics curves as an average of four independent simulations are shown in Figure 4, as well as the detailed analysis about the most accessible sites on the collagen provided by MM-PBSA analysis. The typical final structure in MD simulation is shown in Figure S2. Herein, LRENSCY, with a low ranking of EVINA = −3.7 kcal/mol (Table S1) was chosen as the control. All three inhibitors can bind on collagen surface and inhibit the binding of integrin (Figure 4), but vary in the degree of inhibition. LWWNSYY has been considered as the best potential inhibitor according to Figure 3. Its inhibition ability is then evaluated based on the results shown in Figure 4a. Fast decrease of both dmin and EMD between inhibitor and collagen is observed within 5 ns, indicating fast binding of inhibitor, which confirms its high affinity to collagen surfaces. Meanwhile, a large decrease of dmin between integrin and collagen is observed. For example, at 5 ns, the integrin approaches the collagen with dmin = 0.5 nm, and forms favorable contacts indicated by the decrease of EMD. However, lower values of both dmin and EMD of inhibitor are observed compared to those of integrin. That is, more stable binding of inhibitors is observed, leading to the successful inhibition. After 20 ns, the firm binding of inhibitor is formed and the binding of integrin is seriously blocked. Moreover, the most accessible sites of LWWNSYY on the collagen are mainly favorable for binding (red colored) and locate at the binding sites of integrin, accounting for the successful inhibition. The final structure provides a clear description on the inhibition (Figure S2), where inhibitors bind on the collagen with a location between integrin and collagen, hindering the binding of integrin. Different inhibition is observed in the presence of LRWNSPY. From 4 ns, the integrin approaches the collagen and forms favorable contacts while the inhibitor is still far from the collagen (Figure 4b). So, firm binding of integrin on the collagen surface is observed (ca. at 12 ns). However, from 5 ns, the inhibitor moves toward the collagen indicated by the decrease of dmin. During this process, favorable contacts are also formed between the inhibitor and the collagen, indicated by the decrease of EMD. From 15 ns, binding of inhibitor is formed, leading to the release of integrin. However, the most accessible sites of LRWNSPY on collagen are mainly favorable (red colored) for binding but are not close to the binding sites of integrin. Then, the binding of inhibitor is not stable but has significant fluctuations. For example, the inhibitor moves away from the collagen surface and releases the blocked binding site at 27 ns, but forms binding again at 36 ns. Thereafter, the binding of integrin is blocked by the inhibitor, and effective inhibition is achieved. For the LYWNSGY, as shown in Figure 4c, fast decrease of both dmin and EMD between integrin and collagen is observed, indicating fast binding of integrin. Meanwhile, dmin between the inhibitor and the collagen also decreases. At 11 ns, dmin decreases to 0.17 nm, indicating binding of inhibitor on the collagen surface. However, it moves away from 14 ns. Finally, both integrin and inhibitor bind on the collagen, indicated by low dmin and EMD, but no obvious accessible sites are observed for LYWNSGY. Therefore, the inhibition is not so good as compared with LWWNSYY and LRWNSPY.

Figure 3. Comparison of the final binding conformation of the selected candidates in MD simulations to the docked conformation, as well as the original structure in affinity binding model. Three selected candidates are shown where a lateral view is shown on the right. The final binding conformation in MD simulation is shown in green as a stick model. The others are shown as those in Figure 1.

as the original structure in the ABM (blue). All three candidates can form similar binding, as both the docked conformation and the original structure in the ABM. LWWNSYY shows good superposition of N4, S5, and Y7, which is considered as the best potential inhibitor. LYWNSGY shows good superposition of N4 and S5, while LYWNSGY shows good superposition of S5 and Y7, which also have potential abilities to inhibit the integrin−collagen interactions. 3.5. Inhibition of Integrin Binding on Collagen. Each of the three potential inhibitors was then added into a simulation box containing separated integrin and collagen. As shown in part I, the separated integrin can bind on the collagen surface within 25 ns in physiological saline. Therefore, in the presence of potential inhibitors, the binding dynamics of integrin on the collagen surface was examined for 50 ns to provide direct 4738

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Figure 4. Binding dynamics of integrin on collagen surface in the presence of LWWNSYY (a), LRWNSPY (b), and LYWNSGY (c). LRENSCY is used as control and shown in (d). The time courses of dmin and EMD are shown at the bottom, while the most accessible sites on the collagen by potential inhibitors are shown at the top. Collagen is shown as a ribbon structure. Residue making |ΔGbind| ≥ 0.5 kcal/mol is shown as a licorice structure and colored by its contribution to binding free energy, which ranges from red (most negative) to green (most positive). O stands for hydroxyproline.

Figure 3, where LWWNSYY shows good superposition of N4, S5, and Y7. The binding probability of integrin/inhibitor on the collagen was further calculated based on four independent simulation trajectories to provide a quantitative description of the inhibition, as shown in Figure 5. The lowest Pbind of integrin as well as high Pbind of inhibitor is observed in the presence of LWWNSYY, indicating that the inhibition of integrin binding is indeed attributed to the hindering by the inhibitor. High Pbind of other two inhibitors is also observed, leading to low Pbind of integrin. However, it should be noted that although the inhibitor has high affinity to the collagen, the inhibition can be varied because different binding sites on the collagen surface are observed (Figure 4). As control, Pbind of 100% of the integrin is observed in the presence of LRENSCY, indicating no inhibition. Meanwhile, the Pbind of the inhibitor is the lowest,

As a control, no successful inhibition is observed in the presence of LRENSCY. The inhibitor tries several times to bind on the collagen surface, but has always failed due to the weak interaction. From 25 ns, the firm binding of integrin on the collagen is observed. Meanwhile, the inhibitor moves away from the collagen, which can be seen clearly in the final structure (Figure S2). The most accessible sites of LRENSCY are close to the binding sites of integrin, but unfavorable for the binding (green colored), accounting for the moving away of LRENSCY. Hence, LRENSCY cannot inhibit the binding of integrin. Therefore, from the dynamics trajectories, it can be confirmed that all three inhibitors are capable of blocking the binding of integrin on collagen surface. LWWNSYY is the best of the three inhibitors, which is consistent with the analysis in 4739

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Figure 5. Binding probabilities of integrin on collagen surface in the presence of the three potential inhibitors, LWWNSYY, LRWNSPY, and LYWNSGY. LRENSCY is used as control.

Figure 6. Optical density of PRP after adding PBS (white), collagen (light gray), blocked collagen (dark gray), or LWWNSYY (black). The error bars indicate the standard deviations of four independent assays.

confirming its weak affinity to collagen surfaces. So, LRENSCY has low affinity to the collagen and is thus unable to inhibit, further confirming that the high affinity to the collagen is crucial for the ability of inhibition. Therefore, the inhibition abilities of LWWNSYY, LRWNSPY, and LYWNSGY are verified. LWWNSYY is the best platelet adhesion inhibitor by successfully blocking the integrin−collagen interactions. 3.6. Experimental Validation on the Binding of LWWNSYY on Collagen Surfaces. A triple helical structure of collagen peptide at 10 °C was first confirmed by CD spectra (Figure S3), which is consistent with the results published previously.50 Thereafter, ITC experiments were performed to validate the affinity of LWWNSYY for the triple helical collagen peptide. The collagen peptide containing GFOGER recognition sequence was titrated by LWWNSYY. The titration profile is shown in Figure S4, and the thermodynamic parameters are summarized in Table 3.

Declined optical density of PRP from 0.144 ± 0.001 (PBS) to 0.046 ± 0.004 (collagen) is observed, confirming platelet adhesion induced by collagen. In contrary, no decrease of the optical density is observed in the presence of blocked collagen (0.152 ± 0.010), indicating that LWWNSYY can indeed inhibit platelet adhesion. Moreover, similar optical density is observed in the presence of LWWNSYY (0.153 ± 0.010), indicating that LWWNSYY itself has no effect on platelet adhesion. Therefore, the inhibition by LWWNSYY is achieved by blocking the binding sites of integrin on the collagen surface. LWWNSYY is demonstrated as a potential inhibitor capable of blocking the binding of integrin α2β1 on collagen surfaces and subsequent thrombus formation.

4. CONCLUSIONS Table 3. Thermodynamic Binding Constants for LWWNSYY on Triple Helical Collagen Peptide Measured by ITC Kd (μM)

ΔG (kcal/mol)

ΔH (kcal/mol)

TΔS (kcal/mol)

3.34 ± 1.22

−7.10 ± 0.17

1.45 ± 0.17

8.55 ± 0.01

Discovery of high-efficacy platelet adhesion inhibitor is of great significance for the cure of thrombotic diseases. In the present study, a biomimetic design strategy of high-efficacy inhibitors was proposed, based on the ABM proposed in part I. The biomimetic design scheme can capture the binding affinity behavior of the native integrin−collagen complex. The virtual screening scheme, as a combination of molecular docking, structure similarity analysis, and MD simulations, is proven capable of screening a large number of candidates within a small time scale and with low computational resources, but successful at finding the high-efficiency inhibitor. Herein, the fast screening is facilitated by the fast dock screening, using its crude estimation on the binding affinity of candidate. A precise evaluation is achieved by combination of structure similarity analysis and MD simulations. All three screened inhibitors are capable of blocking the binding of integrin on collagen surface, indicating that the biomimetic design strategy is feasible, fast, and convenient for the screening of platelet adhesion inhibitors. Finally, the best inhibitor revealed in virtual screening, LWWNSYY is demonstrated by ITC examination and its inhibition of platelet adhesion has been experimentally validated. It is expected that the combination of these methodologies would greatly facilitate the discovery of highefficacy inhibitor for integrin−collagen interactions. Further work can be directed toward new structured peptide ligands such as cyclic peptides by using the biomimetic design strategy.

A slightly positive value of ΔH, 1.45 kcal/mol, and larger positive value of TΔS, 8.55 ± 0.01 kcal/mol, are observed at 10 °C, indicating entropy-driven binding of LWWNSYY on collagen surface. The entropy in ITC experiment is obtained from the heat change of reaction and represents the hydrophobic effect of binding. 51 That is, electrostatic interaction and hydrogen bonding are enthalpy-driven, while hydrophobic interaction is entropy-driven.52,53 Therefore, the ITC results indicate that hydrophobic interaction is the dominant factor in affinity binding of LWWNSYY on collagen surface, which is consistent with the simulation results described above. The ΔG value of −7.10 ± 0.17 kcal/mol confirms favorable binding of LWWNSYY on collagen surface. The Kd value of 3.34 ± 1.22 μM is also comparable to that of 7.8 μM of integrin α2A domain on collagen surface reported elsewhere.48 Therefore, LWWNSYY is considered to be a potent high-efficiency inhibitor on the integrin α2β1-collagen interactions. 3.7. Inhibition of Platelet Adhesion by LWWNSYY. The optical density of PRP after separately adding PBS, collagen, blocked collagen or LWWNSYY was measured, as shown in Figure 6. 4740

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ASSOCIATED CONTENT

S Supporting Information *

Summary of Docking Scores Predicted by VINA (Table S1) and Rosetta FlexPepDock (Table S2), distribution of docking scores and RMSD (Figure S1), typical snapshots in the binding dynamic of integrin on collagen surface in the presence of potential inhibitors (Figure S2), CD spectra of triple helical collagen peptide (Figure S3), and thermodynamic ITC characterization of LWWNSYY interactions with triple helical collagen peptide (Figure S4). This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Tel and Fax: +86 22 27404981; E-mail address: [email protected]. cn. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the Natural Science Foundation of China (Nos. 21236005 and 21006069), the Natural Science Foundation of Tianjin (13JCZDJC31100), the Key Technologies R&D Program of International Cooperation of Tianjin, China (11ZCGHHZ00600), and the Innovation Foundation of Tianjin University.

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