iATTRACT: Simultaneous global and local interface optimization for protein–protein docking refinement

Protein‐protein interactions are abundant in the cell but to date structural data for a large number of complexes is lacking. Computational docking methods can complement experiments by providing structural models of complexes based on structures of the individual partners. A major caveat for docking success is accounting for protein flexibility. Especially, interface residues undergo significant conformational changes upon binding. This limits the performance of docking methods that keep partner structures rigid or allow limited flexibility. A new docking refinement approach, iATTRACT, has been developed which combines simultaneous full interface flexibility and rigid body optimizations during docking energy minimization. It employs an atomistic molecular mechanics force field for intermolecular interface interactions and a structure‐based force field for intramolecular contributions. The approach was systematically evaluated on a large protein‐protein docking benchmark, starting from an enriched decoy set of rigidly docked protein–protein complexes deviating by up to 15 Å from the native structure at the interface. Large improvements in sampling and slight but significant improvements in scoring/discrimination of near native docking solutions were observed. Complexes with initial deviations at the interface of up to 5.5 Å were refined to significantly better agreement with the native structure. Improvements in the fraction of native contacts were especially favorable, yielding increases of up to 70%. Proteins 2015; 83:248–258. © 2014 Wiley Periodicals, Inc.     

A holistic molecular docking approach for predicting protein-protein complex structure

A holistic protein-protein molecular docking approach, HoDock, was established, composed of such steps as binding site prediction, initial complex structure sampling, refined complex structure sampling, structure clustering, scoring and final structure selection. This article explains the detailed steps and applications for CAPRI Target 39. The CAPRI result showed that three predicted binding site residues, A191HIS, B512ARG and B531ARG, were correct, and there were five submitted structures with a high fraction of correct receptor-ligand interface residues, indicating that this docking approach may improve prediction accuracy for protein-protein complex structures.     

Understanding the binding of quinoline amines with human serum albumin by spectroscopic and induced fit docking methods

Seven new quinoline-based bioorganic compounds were prepared by solvent-free synthesis and characterized using spectral techniques. The binding of these compounds with human serum albumin (HSA) was investigated by multi-spectroscopic methods. The quenching of Trp fluorescence upon addition of these compounds to HSA confirmed their significant binding. The quenching analysis at three different temperatures revealed that the complex formation is static and the reaction is entropy driven, spontaneous, and exothermic. Hydrogen bonds and van der Waals forces mainly contributed in the interactions as confirmed by the negative ΔH and ΔS values as well as molecular docking. The results from the circular dichroism (CD) spectroscopy indicated the minimal conformational changes of the protein upon binding with these quinoline compounds. The specific binding site and mode of interactions with HSA were also modeled using induced fit molecular docking procedure and their binding site was found to be in the interface of domains II and III, which is similar to the binding of the drug iodipamide with serum albumin.

Communicated by Ramaswamy H. Sarma     

Flexible docking allowing induced fit in proteins: Insights from an open to closed conformational isomers

Here we dock a ligand onto a receptor surface allowing hinge-bending domain/substructural movements. Our approach mimics and manifests induced fit in molecular recognition. All angular rotations are allowed on the one hand, while a conformational space search is avoided on the other. Rather than dock each of the molecular parts separately with subsequent reconstruction of the consistently docked molecules, all parts are docked simultaneously while still utilizing the position of the hinge from the start. Like pliers closing on a screw, the receptor automatically closes on its ligand in the best surface-matching way. Movements are allowed either in the ligand or in the larger receptor, hence reproducing induced molecular fit. Hinge bending movements are frequently observed when molecules associate. There are numerous examples of open versus closed conformations taking place upon binding. Such movements are observed when the substrate binds to its respective enzyme. In particular, such movements are of interest in allosteric enzymes. The movements can involve entire domains, subdomains, loops, (other) secondary structure elements, or between any groups of atoms connected by flexible joints. We have implemented the hinges at points and at bonds. By allowing 3-dimensional (3-D) rotation at the hinge, several rotations about (consecutive or nearby) bonds are implicitly taken into account. Alternatively, if required, the point rotation can be restricted to bond rotation. Here we illustrate this hinge-bending docking approach and the insight into flexibility it provides on a complex of the calmodulin with its M13 ligand, positioning the hinges either in the ligand or in the larger receptor. This automated and efficient method is adapted from computer vision and robotics. It enables utilizing entire molecular surfaces rather than focusing a priori on active sites. Hence, allows attaining the overall optimally matching surfaces, the extent and type of motions which are involved. Here we do not treat the conformational flexibility of side-chains or of very small pieces of the molecules. Therefore, currently available methods addressing these issues and the method presented here, are complementary to each other, expanding the repertoire of computational docking tools foreseen to aid in studies of recognition, conformational flexibility and drug design. Proteins 32:159–174, 1998. © 1998 Wiley-Liss, Inc.     

Atomic solvation parameters in the analysis of protein-protein docking results.

Several sets of amino acid surface areas and transfer free energies were used to derive a total of nine sets of atomic solvation parameters (ASPs). We tested the accuracy of each of these sets of parameters in predicting the experimentally determined transfer free energies of the amino acid derivatives from which the parameters were derived. In all cases, the calculated and experimental values correlated well. We then chose three parameter sets and examined the effect of adding an energetic correction for desolvation based on these three parameter sets to the simple potential function used in our multiple start Monte Carlo docking method. A variety of protein-protein interactions and docking results were examined. In the docking simulations studied, the desolvation correction was only applied during the final energy calculation of each simulation. For most of the docking results we analyzed, the use of an octanol-water-based ASP set marginally improved the energetic ranking of the low-energy dockings, whereas the other ASP sets we tested disturbed the ranking of the low-energy dockings in many of the same systems. We also examined the correlation between the experimental free energies of association and our calculated interaction energies for a series of proteinase-inhibitor complexes. Again, the octanol-water-based ASP set was compatible with our standard potential function, whereas ASP sets derived from other solvent systems were not.     

Protein-protein docking with a reduced protein model accounting for side-chain flexibility

A protein-protein docking approach has been developed based on a reduced protein representation with up to three pseudo atoms per amino acid residue. Docking is performed by energy minimization in rotational and translational degrees of freedom. The reduced protein representation allows an efficient search for docking minima on the protein surfaces within. During docking, an effective energy function between pseudo atoms has been used based on amino acid size and physico-chemical character. Energy minimization of protein test complexes in the reduced representation results in geometries close to experiment with backbone root mean square deviations (RMSDs) of approximately 1 to 3 A for the mobile protein partner from the experimental geometry. For most test cases, the energy-minimized experimental structure scores among the top five energy minima in systematic docking studies when using both partners in their bound conformations. To account for side-chain conformational changes in case of using unbound protein conformations, a multicopy approach has been used to select the most favorable side-chain conformation during the docking process. The multicopy approach significantly improves the docking performance, using unbound (apo) binding partners without a significant increase in computer time. For most docking test systems using unbound partners, and without accounting for any information about the known binding geometry, a solution within approximately 2 to 3.5 A RMSD of the full mobile partner from the experimental geometry was found among the 40 top-scoring complexes. The approach could be extended to include protein loop flexibility, and might also be useful for docking of modeled protein structures.     

Enhanced sampling of protein conformational states for dynamic cross-docking within the protein-protein docking server SwarmDock

The formation of specific protein-protein interactions is often a key to a protein's function. During complex formation, each protein component will undergo a change in the conformational state, for some these changes are relatively small and reside primarily at the sidechain level; however, others may display notable backbone adjustments. One of the classic problems in the protein-docking field is to be able to a priori predict the extent of such conformational changes. In this work, we investigated three protocols to find the most suitable input structure conformations for cross-docking, including a robust sampling approach in normal mode space. Counterintuitively, knowledge of the theoretically best combination of normal modes for unbound-bound transitions does not always lead to the best results. We used a novel spatial partitioning library, Aether Engine (see Supplementary Materials ), to efficiently search the conformational states of 56 receptor/ligand pairs, including a recent CAPRI target, in a systematic manner and selected diverse conformations as input to our automated docking server, SwarmDock, a server that allows moderate conformational adjustments during the docking process. In essence, here we present a dynamic cross-docking protocol, which when benchmarked against the simpler approach of just docking the unbound components shows a 10% uplift in the quality of the top docking pose.     

The relationship between the flexibility of proteins and their conformational states on forming protein-protein complexes with an application to protein-protein docking

We investigate the extent to which the conformational fluctuations of proteins in solution reflect the conformational changes that they undergo when they form binary protein-protein complexes. To do this, we study a set of 41 proteins that form such complexes and whose three-dimensional structures are known, both bound in the complex and unbound. We carry out molecular dynamics simulations of each protein, starting from the unbound structure, and analyze the resulting conformational fluctuations in trajectories of 5 ns in length, comparing with the structure in the complex. It is found that fluctuations take some parts of the molecules into regions of conformational space close to the bound state (or give information about it), but at no point in the simulation does each protein as whole sample the complete bound state. Subsequent use of conformations from a clustered MD ensemble in rigid-body docking is nevertheless partially successful when compared to docking the unbound conformations, as long as the unbound conformations are themselves included with the MD conformations and the whole globally rescored. For one key example where sub-domain motion is present, a ribonuclease inhibitor, principal components analysis of the MD was applied and was also able to produce conformations for docking that gave enhanced results compared to the unbound. The most significant finding is that core interface residues show a tendency to be less mobile (by size of fluctuation or entropy) than the rest of the surface even when the other binding partner is absent, and conversely the peripheral interface residues are more mobile. This surprising result, consistent across up to 40 of the 41 proteins, suggests different roles for these regions in protein recognition and binding, and suggests ways that docking algorithms could be improved by treating these regions differently in the docking process.     

Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Performance of ZDOCK and IRAD in CAPRI rounds 39-45

We report docking performance on the six targets of Critical Assessment of PRedicted Interactions (CAPRI) rounds 39-45 that involved heteromeric protein-protein interactions and had the solved structures released since the rounds were held. Our general strategy involved protein-protein docking using ZDOCK, reranking using IRAD, and structural refinement using Rosetta. In addition, we made extensive use of experimental data to guide our docking runs. All the experimental information at the amino-acid level proved correct. However, for two targets, we also used protein-complex structures as templates for modeling interfaces. These resulted in incorrect predictions, presumably due to the low sequence identity between the targets and templates. Albeit a small number of targets, the performance described here compared somewhat less favorably with our previous CAPRI reports, which may be due to the CAPRI targets being increasingly challenging.     

Integrative modeling of protein-protein interactions with pyDock for the new docking challenges

The seventh CAPRI edition imposed new challenges to the modeling of protein-protein complexes, such as multimeric oligomerization, protein-peptide, and protein-oligosaccharide interactions. Many of the proposed targets needed the efficient integration of rigid-body docking, template-based modeling, flexible optimization, multiparametric scoring, and experimental restraints. This was especially relevant for the multimolecular assemblies proposed in the CASP12-CAPRI37 and CASP13-CAPRI46 joint rounds, which were described and evaluated elsewhere. Focusing on the purely CAPRI targets of this edition (rounds 38-45), we have participated in all 17 assessed targets (considering heteromeric and homomeric interfaces in T125 as two separate targets) both as predictors and as scorers, by using integrative modeling based on our docking and scoring approaches: pyDock, IRaPPA, and LightDock. In the protein-protein and protein-peptide targets, we have also participated with our webserver (pyDockWeb). On these 17 CAPRI targets, we submitted acceptable models (or better) within our top 10 models for 10 targets as predictors, 13 targets as scorers, and 4 targets as servers. In summary, our participation in this CAPRI edition confirmed the capabilities of pyDock for the scoring of docking models, increasingly used within the context of integrative modeling of protein interactions and multimeric assemblies.     

Discovery of promising FtsZ inhibitors by E-pharmacophore, 3D-QSAR,molecular docking study,and molecular dynamics simulation

Filamentous temperature-sensitive protein Z (FtsZ), playing a key role in bacterial cell division, is regarded as a promising target for the design of antimicrobial agent. This study is looking for potential high-efficiency FtsZ inhibitors. Ligand-based pharmacophore and E-pharmacophore, virtual screening and molecular docking were used to detect promising FtsZ inhibitors, and molecular dynamics simulation was used to study the stability of protein-ligand complexes in this paper. Sixty-three inhibitors from published literatures with pIC₅₀ ranging from 2.483 to 5.678 were collected to develop ligand-based pharmacophore model. 4DXD bound with 9PC was selected to develop the E-pharmacophore model. The pharmacophore models validated by test set method and decoy set were employed for virtual screening to exclude inactive compounds against ZINC database. After molecular docking, ADME analysis, IFD docking and MM-GBSA, 8 hits were identified as potent FtsZ inhibitors. A 50?ns molecular dynamics simulation was implemented on the compounds to assess the stability between potent inhibitors and FtsZ. The results indicated that the candidate compounds had a high docking score and were strongly combined with FtsZ by forming hydrogen bonding interactions with key amino acid residues, and van der Waals forces and hydrophobic interactions had significant contribution to the stability of the binding. Molecular dynamics simulation results showed that the protein-ligand compounds performed well in both the stability and flexibility of the simulation process.     

Induced fit docking,free energy calculation and molecular dynamics studies on Mycobacterium tuberculosis alanine racemase inhibitor

Alar, a Pyridoxal 5′-phosphate (PLP)-dependent bacterial enzyme is responsible for the racemisation of L-alanine into D-alanine which is essential for the peptidoglycan biosynthesis in both Gram-positive and Gram-negative bacteria. In the present study, we performed induced fit docking, binding free energy calculation and molecular dynamics simulation to elucidate the Alar inhibition potential of 1,2,4-thiadiazolidine-3,5-dione-based inhibitor 1. The inhibitor binds to the hydrophobic groove of Alar and the binding was found to be stable throughout 20-ns MD simulation. Induced fit docking result showed that Lys42, Tyr46, Tyr175 and Tyr364 residues are primarily responsible for the stabilisation of inhibitor–protein complex. Further, high negative van der Waals binding free energy value of –38.88 kcal/mol, indicated it as the main driving force for the inhibitor binding. Based on the information obtained from this study, we designed few molecules as potent Alar inhibitor. In order to gain structural insight and to validate the stability of complex, we performed 20-ns MD simulation of the designed molecule D1. Results obtained from this study can be used for the design of M. tuberculosis Alar potent inhibitors lacking affinity for the co-factor PLP.     

Flexible protein-flexible ligand docking with disrupted velocity simulated annealing

By docking flexible balanol to a rigid model of protein kinase A (PKA), we found that a new simulated annealing protocol termed disrupted velocity simulated annealing (DIVE-SA) outperformed the replica-exchange method and the traditional simulated annealing method in identifying the correct docking pose. In this protocol, the atomic velocities were reassigned periodically to encourage the system to sample a large conformational space. We also found that scaling potential energy surface to reduce structural transition barriers could further facilitate docking. The DIVE-SA method was then evaluated on its ability to perform flexible ligand-flexible protein docking of three ligands (balanol, a balanol analog, and ATP) to PKA. To reduce computational time and to avoid possible unphysical structural changes resulting from the use of nonoptimal force fields, a soft restrain was applied to keep the root-mean-square-deviation (RMSD) between instantaneous protein structures and a chosen reference structure small. Because the restrain was applied to the overall RMSD rather than to individual atoms, a protein could still experience relatively large conformational changes during docking. To examine the impact of applying such a restrain on docking, we constructed two semi-flexible protein models by choosing two different crystal structures as reference. Both the balanol analog and ATP were able to dock to either one of these semi-flexible protein models. On the other hand, balanol could only dock well to one of them. Further analysis indicated that the restrain on the glycine-rich loop was too strong, preventing it to adjust its structure to accommodate balanol in the binding pocket of PKA. Removing the restrain on the glycine-rich loop resulted in much better docking poses. This finding demonstrates the important role that the flexibility of the glycine-rich loop play in accepting different ligands and should profitably not be restrained in molecular docking so that more diverse ligands can be studied.     

Model for the yeast cofactor A-beta-tubulin complex based on computational docking and mutagensis

Virtually every biological process involves protein-protein contact but relatively few protein-protein complexes have been solved by X-ray crystallography. As more individual protein structures become available, computational methods are likely to play increasingly important roles in defining these interactions. Tubulin folding and dimer formation are complex processes requiring a variety of protein cofactors. One of these is cofactor A, which interacts with beta-tubulin prior to assembly of the alpha-tubulin-beta-tubulin heterodimer. In the yeast Saccharomyces cerevisiae, beta-tubulin is encoded by TUB2 and cofactor A by RBL2. We have used computational docking and site-directed mutagenesis to generate a model of the Rbl2-Tub2 complex from the solved structures of these two proteins. Residues in the N termini and the loops of the Rbl2 homodimer appear to mediate binding to beta-tubulin. These interact with beta-tubulin residues in the region that contains helices H9 and H10. Rbl2 and alpha-tubulin share overlapping binding sites on the beta-tubulin molecule providing a structural explanation for the mutually exclusive binding of Rbl2 and alpha-tubulin to beta-tubulin.     

An explorative study on Staphylococcus aureus MurE inhibitor: induced fit docking,binding free energy calculation,and molecular dynamics

Staphylococcus aureus MurE enzyme catalyzes the addition of l-lysine as third residue of the peptidoglycan peptide moiety. Due to the high substrate specificity and its ubiquitous nature among bacteria, MurE enzyme is considered as one of the potential target for the development of new therapeutic agents. In the present work, induced fit docking (IFD), binding free energy calculation, and molecular dynamics (MD) simulation were carried out to elucidate the inhibition potential of 2-thioxothiazolidin-4-one based inhibitor 1 against S. aureus MurE enzyme. The inhibitor 1 formed majority of hydrogen bonds with the central domain residues Asn151, Thr152, Ser180, Arg187, and Lys219. Binding free-energy calculation by MM-GBSA approach showed that van der Waals (ΔG_vdW, ?57.30?kcal/mol) and electrostatic solvation (ΔG_solv, ?36.86?kcal/mol) energy terms are major contributors for the inhibitor binding. Further, 30-ns MD simulation was performed to validate the stability of ligand–protein complex and also to get structural insight into mode of binding. Based on the IFD and MD simulation results, we designed four new compounds D1–D4 with promising binding affinity for the S. aureus MurE enzyme. The designed compounds were subjected to the extra-precision docking and binding free energy was calculated for complexes. Further, a 30-ns MD simulation was performed for D1/4C13 complex.     

A multi-spectroscopic and molecular docking approach to investigate the interaction of antiviral drug oseltamivir with ct-DNA

The possible interaction between the antiviral drug oseltamivir and calf thymus DNA at physiological pH was studied by spectrophotometry, competitive spectrofluorimetry, differential pulse voltammogram (DPV), circular dichroism spectroscopy (CD), viscosity measurements, salt effect, and computational studies. Intercalation of oseltamivir between the base pairs of DNA was shown by a sharp increase in specific viscosity of DNA and a decrease of the peak current and a positive shift in differential pulse voltammogram. Competitive fluorescence experiments were performed using neutral red (NR) as a probe for the intercalation binding mode. The studies showed that oseltamivir is able to release the NR.     

Combined spectroscopies and molecular docking approach to characterizing the binding interaction of enalapril with bovine serum albumin

The binding interaction between bovine serum albumin (BSA) and enalapril (ENPL) at the imitated physiological conditions (pH = 7.4) was investigated using UV–vis absorption spectroscopy (UV–vis), fluorescence emission spectroscopy (FES), synchronous fluorescence spectroscopy (SFS), Fourier transform infrared spectroscopy (FT‐IR), circular dichroism (CD) and molecular docking methods. It can be deduced from the experimental results from the steady‐state fluorescence spectroscopic titration that the intrinsic BSA fluorescence quenching mechanism induced by ENPL is static quenching, based on the decrease in the BSA quenching constants in the presence of ENPL with increase in temperature and BSA quenching rates >10¹⁰ L mol^?1 sec^?1. This result indicates that the ENPL–BSA complex is formed through an intermolecular interaction of ENPL with BSA. The main bonding forces for interaction of BSA and ENPL are van der Waal's forces and hydrogen bonding interaction based on negative values of Gibbs free energy change (ΔG ⁰), enthalpic change (ΔH ⁰) and entropic change (ΔS ⁰). The binding of ENPL with BSA is an enthalpy‐driven process due to |ΔH °| > |T ΔS °| in the binding process. The results of competitive binding experiments and molecular docking confirm that ENPL binds in BSA sub‐domain IIA (site I) and results in a slight change in BSA conformation, but BSA still retains its α‐helical secondary structure.     

A memetic algorithm enables efficient local and global all-atom protein-protein docking with backbone and side-chain flexibility

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New approach to evaluating the effects of a drug on protein complexes with quantitative proteomics,using the SILAC method and bioinformatic approach

ABSTRACT

Protein–protein interactions (PPIs) lead the formation of protein complexes that perform biochemical reactions that maintain the living state of the living cell. Although therapeutic drugs should influence the formation of protein complexes in addition to PPI network, the methodology analyzing such influences remain to be developed. Here, we demonstrate that a new approach combining HPLC (high performance liquid chromatography) for separating protein complexes, and the SILAC (stable isotope labeling using amino acids in cell culture) method for relative protein quantification, enable us to identify the protein complexes influenced by a drug. We applied this approach to the analysis of thalidomide action on HepG2 cells, assessed the identified proteins by clustering data analyses, and assigned 135 novel protein complexes affected by the drug. We propose that this approach is applicable to elucidating the mechanisms of actions of other therapeutic drugs on the PPI network, and the formation of protein complexes.