FLIPDock: docking flexible ligands into flexible receptors

Conformational changes of biological macromolecules when binding with ligands have long been observed and remain a challenge for automated docking methods. Here we present a novel protein-ligand docking software called FLIPDock (Flexible LIgand-Protein Docking) allowing the automated docking of flexible ligand molecules into active sites of flexible receptor molecules. In FLIPDock, conformational spaces of molecules are encoded using a data structure that we have developed recently called the Flexibility Tree (FT). While the FT can represent fully flexible ligands, it was initially designed as a hierarchical and multiresolution data structure for the selective encoding of conformational subspaces of large biological macromolecules. These conformational subspaces can be built to span a range of conformations important for the biological activity of a protein. A variety of motions can be combined, ranging from domains moving as rigid bodies or backbone atoms undergoing normal mode-based deformations, to side chains assuming rotameric conformations. In addition, these conformational subspaces are parameterized by a small number of variables which can be searched during the docking process, thus effectively modeling the conformational changes in a flexible receptor. FLIPDock searches the variables using genetic algorithm-based search techniques and evaluates putative docking complexes with a scoring function based on the AutoDock3.05 force-field. In this paper, we describe the concepts behind FLIPDock and the overall architecture of the program. We demonstrate FLIPDock's ability to solve docking problems in which the assumption of a rigid receptor previously prevented the successful docking of known ligands. In particular, we repeat an earlier cross docking experiment and demonstrate an increased success rate of 93.5%, compared to original 72% success rate achieved by AutoDock over the 400 cross-docking calculations. We also demonstrate FLIPDock's ability to handle conformational changes involving backbone motion by docking balanol to an adenosine-binding pocket of protein kinase A.     

A flexible docking scheme to explore the binding selectivity of PDZ domains

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTA LIGAND , we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density‐95/Dlg/ZO‐1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.     

Effective handling of induced-fit motion in flexible docking

For structure-based drug design, where various ligand structures need to be docked to a target protein structure, a docking method that can handle conformational flexibility of not only the ligand, but also the protein, is indispensable. We have developed a simple and effective approach for dealing with the local induced-fit motion of the target protein, and implemented it in our docking tool, ADAM. Our approach efficiently combines the following two strategies: a vdW-offset grid in which the protein cavity is enlarged uniformly, and structure optimization allowing the motion of ligand and protein atoms. To examine the effectiveness of our approach, we performed docking validation studies, including redocking in 18 test cases and foreign-docking, in which various ligands from foreign crystal structures of complexes are docked into a target protein structure, in 22 cases (on five target proteins). With the original ADAM, the correct docking modes (RMSD < 2.0 A) were not present among the top 20 models in one case of redocking and four cases of foreign-docking. When the handling of induced-fit motion was implemented, the correct solutions were acquired in all 40 test cases. In foreign-docking on thymidine kinase, the correct docking modes were obtained as the top-ranked solutions for all 10 test ligands by our combinatorial approach, and this appears to be the best result ever reported with any docking tool. The results of docking validation have thus confirmed the effectiveness of our approach, which can provide reliable docking models even in the case of foreign-docking, where conformational change of the target protein cannot be ignored. We expect that this approach will contribute substantially to actual drug design, including virtual screening.     

Insight into the mechanism of lipids binding and uptake by CD36 receptor

The membrane protein CD36 is a member of the class B scavenger receptor family. It plays a crucial role in some cardiovascular pathologies and metabolic diseases. Studying the mechanism of action of CD36 receptor is limited due to the absence of its tridimensional crystallized structure. The molecular docking method has allowed us to perform various simulation of the CD36 receptor interaction with their ligands involved in the development of some diseases. In this work, we predicted a tridimensional structure model of CD36 extracellular domain. In addition, we have achieved several tests of rigid and flexible docking by acting on residues proposed in previous experimental researches as essential in fixing of LFCAs. Furthermore, we have acted on regions that appear a key binding site of LFCAs. The physicoc hemical evaluation indicated the reliability of the proposed CD36 structure used for different molecular docking tests. Based on the docking outcome, we were able to propose the different steps of the mechanism allowing the interaction of fatty acids on CD36 receptor and their penetration into the cell cytoplasm. The obtained results and taking in consideration CD36 receptor as a therapeutic target will help us to suggest the mechanism by which an antagonist may inhibit this receptor by acting on its extracellular domain.     

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.     

Principles of docking: An overview of search algorithms and a guide to scoring functions

The docking field has come of age. The time is ripe to present the principles of docking, reviewing the current state of the field. Two reasons are largely responsible for the maturity of the computational docking area. First, the early optimism that the very presence of the "correct" native conformation within the list of predicted docked conformations signals a near solution to the docking problem, has been replaced by the stark realization of the extreme difficulty of the next scoring/ranking step. Second, in the last couple of years more realistic approaches to handling molecular flexibility in docking schemes have emerged. As in folding, these derive from concepts abstracted from statistical mechanics, namely, populations. Docking and folding are interrelated. From the purely physical standpoint, binding and folding are analogous processes, with similar underlying principles. Computationally, the tools developed for docking will be tremendously useful for folding. For large, multidomain proteins, domain docking is probably the only rational way, mimicking the hierarchical nature of protein folding. The complexity of the problem is huge. Here we divide the computational docking problem into its two separate components. As in folding, solving the docking problem involves efficient search (and matching) algorithms, which cover the relevant conformational space, and selective scoring functions, which are both efficient and effectively discriminate between native and non-native solutions. It is universally recognized that docking of drugs is immensely important. However, protein-protein docking is equally so, relating to recognition, cellular pathways, and macromolecular assemblies. Proteins function when they are bound to other molecules. Consequently, we present the review from both the computational and the biological points of view. Although large, it covers only partially the extensive body of literature, relating to small (drug) and to large protein-protein molecule docking, to rigid and to flexible. Unfortunately, when reviewing these, a major difficulty in assessing the results is the non-uniformity in the formats in which they are presented in the literature. Consequently, we further propose a way to rectify it here.     

Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP

Most current docking methods to identify possible ligands and putative binding sites on a receptor molecule assume a rigid receptor structure to allow virtual screening of large ligand databases. However, binding of a ligand can lead to changes in the receptor protein conformation that are sterically necessary to accommodate a bound ligand. An approach is presented that allows relaxation of the protein conformation in precalculated soft flexible degrees of freedom during ligand-receptor docking. For the immunosuppressant FK506-binding protein FKBP, the soft flexible modes are extracted as principal components of motion from a molecular dynamics simulation. A simple penalty function for deformations in the soft flexible mode is used to limit receptor protein deformations during docking that avoids a costly recalculation of the receptor energy by summing over all receptor atom pairs at each step. Rigid docking of the FK506 ligand binding to an unbound FKBP conformation failed to identify a geometry close to experiment as favorable binding site. In contrast, inclusion of the flexible soft modes during systematic docking runs selected a binding geometry close to experiment as lowest energy conformation. This has been achieved at a modest increase of computational cost compared to rigid docking. The approach could provide a computationally efficient way to approximately account for receptor flexibility during docking of large numbers of putative ligands and putative docking geometries.     

Structure-based identification of binding sites,native ligands and potential inhibitors for G-protein coupled receptors

G-protein coupled receptors (GPCRs) are the largest family of cell-surface receptors involved in signal transmission. Drugs associated with GPCRs represent more than one fourth of the 100 top-selling drugs and are the targets of more than half of the current therapeutic agents on the market. Our methodology based on the internal coordinate mechanics (ICM) program can accurately identify the ligand-binding pocket in the currently available crystal structures of seven transmembrane (7TM) proteins [bacteriorhodopsin (BR) and bovine rhodopsin (bRho)]. The binding geometry of the ligand can be accurately predicted by ICM flexible docking with and without the loop regions, a useful finding for GPCR docking because the transmembrane regions are easier to model. We also demonstrate that the native ligand can be identified by flexible docking and scoring in 1.5% and 0.2% (for bRho and BR, respectively) of the best scoring compounds from two different types of compound database. The same procedure can be applied to the database of available chemicals to identify specific GPCR binders. Finally, we demonstrate that even if the sidechain positions in the bRho binding pocket are entirely wrong, their correct conformation can be fully restored with high accuracy (0.28 A) through the ICM global optimization with and without the ligand present. These binding site adjustments are critical for flexible docking of new ligands to known structures or for docking to GPCR homology models. The ICM docking method has the potential to be used to "de-orphanize" orphan GPCRs (oGPCRs) and to identify antagonists-agonists for GPCRs if an accurate model (experimentally and computationally validated) of the structure has been constructed or when future crystal structures are determined.     

Protein flexibility in ligand docking and virtual screening to protein kinases

The main complicating factor in structure-based drug design is receptor rearrangement upon ligand binding (induced fit). It is the induced fit that complicates cross-docking of ligands from different ligand-receptor complexes. Previous studies have shown the necessity to include protein flexibility in ligand docking and virtual screening. Very few docking methods have been developed to predict the induced fit reliably and, at the same time, to improve on discriminating between binders and non-binders in the virtual screening process.We present an algorithm called the ICM-flexible receptor docking algorithm (IFREDA) to account for protein flexibility in virtual screening. By docking flexible ligands to a flexible receptor, IFREDA generates a discrete set of receptor conformations, which are then used to perform flexible ligand-rigid receptor docking and scoring. This is followed by a merging and shrinking step, where the results of the multiple virtual screenings are condensed to improve the enrichment factor. In the IFREDA approach, both side-chain rearrangements and essential backbone movements are taken into consideration, thus sampling adequately the conformational space of the receptor, even in cases of large loop movements.As a preliminary step, to show the importance of incorporating protein flexibility in ligand docking and virtual screening, and to validate the merging and shrinking procedure, we compiled an extensive small-scale virtual screening benchmark of 33 crystal structures of four different protein kinases sub-families (cAPK, CDK-2, P38 and LCK), where we obtained an enrichment factor fold-increase of 1.85±0.65 using two or three multiple experimental conformations. IFREDA was used in eight protein kinase complexes and was able to find the correct ligand conformation and discriminate the correct conformations from the “misdocked” conformations solely on the basis of energy calculation. Five of the generated structures were used in the small-scale virtual screening stage and, by merging and shrinking the results with those of the original structure, we show an enrichment factor fold increase of 1.89±0.60, comparable to that obtained using multiple experimental conformations.Our cross-docking tests on the protein kinase benchmark underscore the necessity of incorporating protein flexibility in both ligand docking and virtual screening. The methodology presented here will be extremely useful in cases where few or no experimental structures of complexes are available, while some binders are known.     

Docking of flexible ligands to flexible receptors in solution by molecular dynamics simulation

In this paper, a method of simulating the docking of small flexible ligands to flexible receptors in water is reported. The method is based on molecular dynamics simulations and is an extension of an algorithm previously reported by Di Nola et al. (Di Nola et al., Proteins 1994;19:174-182). The method allows a fast exploration of the receptor surface, using a high temperature of the center of mass translational motion, while the ligand internal motions, the solvent, and the receptor are simulated at room temperature. In addition, the method allows a fast center of mass motion of the ligand, even in solution. The dampening effect of the solvent can be overcome by applying different weights to the interactions between system subsets (solvent, receptor, and ligand). Specific ligand-receptor distances have been used to compare the results of the simulations with the crystal structure. The method is applied, as a test system, to the docking of the phosphocholine to the immunoglobulin McPC603. The results show the similarity of structure between the complex in solution and in the crystal.     

Taking geometry to its edge: fast unbound rigid (and hinge-bent) docking

We present a very efficient rigid "unbound" soft docking methodology, which is based on detection of geometric shape complementarity, allowing liberal steric clash at the interface. The method is based on local shape feature matching, avoiding the exhaustive search of the 6D transformation space. Our experiments at CAPRI rounds 1 and 2 show that although the method does not perform an exhaustive search of the 6D transformation space, the "correct" solution is never lost. However, such a solution might rank low for large proteins, because there are alternatives with significantly larger geometrically compatible interfaces. In many cases this problem can be resolved by successful a priori focusing on the vicinity of potential binding sites as well as the extension of the technique to flexible (hinge-bent) docking. This is demonstrated in the experiments performed as a lesson from our CAPRI experience.     

Monte Carlo docking with ubiquitin.

The development of general strategies for the performance of docking simulations is prerequisite to the exploitation of this powerful computational method. Comprehensive strategies can only be derived from docking experiences with a diverse array of biological systems, and we have chosen the ubiquitin/diubiquitin system as a learning tool for this process. Using our multiple-start Monte Carlo docking method, we have reconstructed the known structure of diubiquitin from its two halves as well as from two copies of the uncomplexed monomer. For both of these cases, our relatively simple potential function ranked the correct solution among the lowest energy configurations. In the experiments involving the ubiquitin monomer, various structural modifications were made to compensate for the lack of flexibility and for the lack of a covalent bond in the modeled interaction. Potentially flexible regions could be identified using available biochemical and structural information. A systematic conformational search ruled out the possibility that the required covalent bond could be formed in one family of low-energy configurations, which was distant from the observed dimer configuration. A variety of analyses was performed on the low-energy dockings obtained in the experiment involving structurally modified ubiquitin. Characterization of the size and chemical nature of the interface surfaces was a powerful adjunct to our potential function, enabling us to distinguish more accurately between correct and incorrect dockings. Calculations with the structure of tetraubiquitin indicated that the dimer configuration in this molecule is much less favorable than that observed in the diubiquitin structure, for a simple monomer-monomer pair. Based on the analysis of our results, we draw conclusions regarding some of the approximations involved in our simulations, the use of diverse chemical and biochemical information in experimental design and the analysis of docking results, as well as possible modifications to our docking protocol.     

Accounting for loop flexibility during protein-protein docking

Although reliable docking can now be achieved for systems that do not undergo important induced conformational change upon association, the presence of flexible surface loops, which must adapt to the steric and electrostatic properties of a partner, generally presents a major obstacle. We report here the first docking method that allows large loop movements during a systematic exploration of the possible arrangements of the two partners in terms of position and rotation. Our strategy consists in taking into account an ensemble of possible loop conformations by a multi-copy representation within a reduced protein model. The docking process starts from regularly distributed positions and orientations of the ligand around the whole receptor. Each starting configuration is submitted to energy minimization during which the best-fitting loop conformation is selected based on the mean-field theory. Trials were carried out on proteins with significant differences in the main-chain conformation of the binding loop between isolated form and complexed form, which were docked to their partner considered in their bound form. The method is able to predict complexes very close to the crystal complex both in terms of relative position of the two partners and of the geometry of the flexible loop. We also show that introducing loop flexibility on the isolated protein form during systematic docking largely improves the predictions of relative position of the partners in comparison with rigid-body docking.     

蛋白质柔性复合物的结构预测

将自洽系综最优化方法（ＳＣＥＯ）推广到主链可变的分子体系,并以此来实现蛋白质复合物结合界面的柔性优化。据此,提出了一种模拟蛋白质“诱导契合”过程的计算方法,来实现蛋白质柔性复合物的结构预测。经过三个蛋白质柔性复合物结构预测的检验,表明这种方法是可行的,并且达到了计算精度和计算速度上的兼顾     

MADAMM: a multistaged docking with an automated molecular modeling protocol

Dealing with receptor flexibility in docking methodology is still a problem. The main reason behind this difficulty is the large number of degrees of freedom that have to be considered in this kind of calculations. In this paper, we present an automated procedure, called MADAMM, that allows flexibilization of both the receptor and the ligand during a multistaged docking with an automated molecular modeling protocol. We show that the orientation of particular residues at the interface between the protein and the ligand have a crucial influence on the way they interact during the docking process, and the standard docking methodologies failed to predict their correct mode of binding. We present some examples that demonstrate the capabilities of this approach when compared with traditional docking methodologies.     

Fragment-based modeling of NAD binding to the catalytic subunits of diphtheria and pertussis toxins

We describe a novel application of a fragment-based ligand docking technique; similar methods are commonly applied to the de novo design of ligands for target protein binding sites. We have used several new flexible docking and superposition tools, as well as a more conventional rigid-body (fragment) docking method, to examine NAD binding to the catalytic subunits of diphtheria (DT) and pertussis (PT) toxins, and to propose a model of the NAD–PT complex. Docking simulations with the rigid NAD fragments adenine and nicotinamide revealed that the low-energy dockings clustered in three distinct sites on the two proteins. Two of the sites were common to both fragments and were related to the structure of NAD bound to DT in an obvious way; however, the adenine subsite of PT was shifted relative to that of DT. We chose adenine/nicotinamide pairs of PT dockings from these clusters and flexibly superimposed NAD onto these pairs. A Monte Carlo–based flexible docking procedure and energy minimization were used to refine the modeled NAD–PT complexes. The modeled complex accounts for the sequence and structural similarities between PT and DT and is consistent with many results that suggest the catalytic importance of certain residues. A possible functional role for the structural difference between the two complexes is discussed. Proteins 31:282–298, 1998. © 1998 Wiley-Liss, Inc.     

pyDock: electrostatics and desolvation for effective scoring of rigid-body protein-protein docking

The accurate scoring of rigid-body docking orientations represents one of the major difficulties in protein-protein docking prediction. Other challenges are the development of faster and more efficient sampling methods and the introduction of receptor and ligand flexibility during simulations. Overall, good discrimination of near-native docking poses from the very early stages of rigid-body protein docking is essential step before applying more costly interface refinement to the correct docking solutions. Here we explore a simple approach to scoring of rigid-body docking poses, which has been implemented in a program called pyDock. The scheme is based on Coulombic electrostatics with distance dependent dielectric constant, and implicit desolvation energy with atomic solvation parameters previously adjusted for rigid-body protein-protein docking. This scoring function is not highly dependent on specific geometry of the docking poses and therefore can be used in rigid-body docking sets generated by a variety of methods. We have tested the procedure in a large benchmark set of 80 unbound docking cases. The method is able to detect a near-native solution from 12,000 docking poses and place it within the 100 lowest-energy docking solutions in 56% of the cases, in a completely unrestricted manner and without any other additional information. More specifically, a near-native solution will lie within the top 20 solutions in 37% of the cases. The simplicity of the approach allows for a better understanding of the physical principles behind protein-protein association, and provides a fast tool for the evaluation of large sets of rigid-body docking poses in search of the near-native orientation.     

嗜酸氧化亚铁硫杆菌的谷胱甘肽还原酶的结构模建和底物分子对接

极端环境微生物嗜酸氧化亚铁硫杆菌的谷胱甘肽还原酶(GR)可能在它的抵抗极端酸性,有毒和氧化性的生物浸出环境中发挥至关重要的作用.通过同源模建技术和分子动力学模拟,它的一个三维结构被构建,优化和检验了.获得的结构被进一步用于搜索绑定位点,跟辅因子黄素腺嘌呤二核苷酸(FAD)和底物谷胱甘肽(GSSG)进行分子柔性对接,并以此识别关健残基.对接结果显示,位于活性残基Cys42和Cys47之间的二硫键夹在FAD的活性位点和底物GSSG的二硫键之间.它们之间的距离非常靠近,这跟底物反应机理的初始步骤的情况十分一致.相互作用能表明8个酶中残基Cys42,Cys47,GIu443B,Glu444B,His438B,Ser14,Thr447B和Lys51是固定或激活GSSG的关键残基,这跟以前的实验事实相吻合.此外,根据相互作用能我们还新发现7个重要残基(Arg449B,Pro439B,Thr440B,Thr310,Va143,Gly46 and Va148).所有这些残基在其它物种中的相应物中也都是保守的.这些结果有助于进一步的实验研究和理解其催化机理,进而揭示这种细菌的抗毒机理,服务于工业应用.