Molecular docking with ligand attached water molecules

A novel approach to incorporate water molecules in protein-ligand docking is proposed. In this method, the water molecules display the same flexibility during the docking simulation as the ligand. The method solvates the ligand with the maximum number of water molecules, and these are then retained or displaced depending on energy contributions during the docking simulation. Instead of being a static part of the receptor, each water molecule is a flexible on/off part of the ligand and is treated with the same flexibility as the ligand itself. To favor exclusion of the water molecules, a constant entropy penalty is added for each included water molecule. The method was evaluated using 12 structurally diverse protein-ligand complexes from the PDB, where several water molecules bridge the ligand and the protein. A considerable improvement in successful docking simulations was found when including flexible water molecules solvating hydrogen bonding groups of the ligand. The method has been implemented in the docking program Molegro Virtual Docker (MVD).     

DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases

In this paper we describe the search strategies developed for docking flexible molecules to macomolecular sites that are incorporated into the widely distributed DOCK software, version 4.0. The search strategies include incremental construction and random conformation search and utilize the existing Coulombic and Lennard-Jones grid-based scoring function. The incremental construction strategy is tested with a panel of 15 crystallographic testcases, created from 12 unique complexes whose ligands vary in size and flexibility. For all testcases, at least one docked position is generated within 2 Å of the crystallographic position. For 7 of 15 testcases, the top scoring position is also within 2 Å of the crystallographic position. The algorithm is fast enough to successfully dock a few testcases within seconds and most within 100 s. The incremental construction and the random search strategy are evaluated as database docking techniques with a database of 51 molecules docked to two of the crystallographic testcases. Incremental construction outperforms random search and is fast enough to reliably rank the database of compounds within 15 s per molecule on an SGI R10000 cpu.     

Modeling loop backbone flexibility in receptor‐ligand docking simulations

The relevance of receptor conformational change during ligand binding is well documented for many pharmaceutically relevant receptors, but is still not fully accounted for in in silico docking methods. While there has been significant progress in treatment of receptor side chain flexibility sampling of backbone flexibility remains challenging because the conformational space expands dramatically and the scoring function must balance protein–protein and protein–ligand contributions. Here, we investigate an efficient multistage backbone reconstruction algorithm for large loop regions in the receptor and demonstrate that treatment of backbone receptor flexibility significantly improves binding mode prediction starting from apo structures and in cross docking simulations. For three different kinase receptors in which large flexible loops reconstruct upon ligand binding, we demonstrate that treatment of backbone flexibility results in accurate models of the complexes in simulations starting from the apo structure. At the example of the DFG‐motif in the p38 kinase, we also show how loop reconstruction can be used to model allosteric binding. Our approach thus paves the way to treat the complex process of receptor reconstruction upon ligand binding in docking simulations and may help to design new ligands with high specificity by exploitation of allosteric mechanisms. © 2012 Wiley Periodicals, Inc.     

Flexible ligand docking without parameter adjustment across four ligand–receptor complexes

Understanding molecular recognition is one of the fundamental problems in molecular biology. Computationally, molecular recognition is formulated as a docking problem. Ideally, a molecular docking algorithm should be computationally efficient, provide reasonably thorough search of conformational space, obtain solutions with reasonable consistency, and not require parameter adjustments. With these goals in mind, we developed DIVALI (Docking wIth eVolutionary AlgorIthms), a program which efficiently and reliably searches for the possible binding modes of a ligand within a fixed receptor. We use an AMBER-type potential function and search for good ligand conformations using a genetic algorithm (GA). We apply our system to study the docking of both rigid and flexible ligands in four different complexes. Our results indicate that it is possible to find diverse binding modes, including structures like the crystal structure, all with comparable potential function values. To achieve this, certain modifications to the standard GA recipe are essential. © 1995 John Wiley & Sons, Inc.     

芬太尼类化合物与阿片μ受体相互作用的分子对接与分子动力学模拟

采用分子对接和分子动力学(MD)模拟方法研究了芬太尼类化合物与阿片μ受体的相互作用机制.先用AutoDock4.0程序将芬太尼类化合物对接到同源模建的阿片μ受体结构中,再用GROMACS程序包在水溶液体系中分别对12个芬太尼激动剂和阿片μ受体蛋白复合物进行了MD模拟研究,优化对接复合物的结构,最后利用MM-PBSA方法,在APBS程序中计算芬太尼类衍生物与阿片μ受体的结合自由能,计算出的受体配合物结合常数(Ki)与其实验值吻合较好,并预测了化合物的活性排序.结果表明,复合物蛋白结构与空载受体蛋白结构有较大差异,特别是胞内区IL2、IL3和跨膜区段TM4骨架构象变化较大,不同的化合物对受体结构影响也有差异,活性较好的化合物会增加蛋白特定区域结构的柔性.芬太尼类化合物可能是通过和受体结合后诱导阿片μ受体构象转变为活性构象,引起一系列的信号传导激活G蛋白,从而引发生理效应.     

Docking to RNA via root-mean-square-deviation-driven energy minimization with flexible ligands and flexible targets

Structure-based drug design is now well-established for proteins as a key first step in the lengthy process of developing new drugs. In many ways, RNA may be a better target to treat disease than a protein because it is upstream in the translation pathway, so inhibiting a single mRNA molecule could prevent the production of thousands of protein gene products. Virtual screening is often the starting point for structure-based drug design. However, computational docking of a small molecule to RNA seems to be more challenging than that to protein due to the higher intrinsic flexibility and highly charged structure of RNA. Previous attempts at docking to RNA showed the need for a new approach. We present here a novel algorithm using molecular simulation techniques to account for both nucleic acid and ligand flexibility. In this approach, with both the ligand and the receptor permitted some flexibility, they can bind one another via an induced fit, as the flexible ligand probes the surface of the receptor. A possible ligand can explore a low-energy path at the surface of the receptor by carrying out energy minimization with root-mean-square-distance constraints. Our procedure was tested on 57 RNA complexes (33 crystal and 24 NMR structures); this is the largest data set to date to reproduce experimental RNA binding poses. With our procedure, the lowest-energy conformations reproduced the experimental binding poses within an atomic root-mean-square deviation of 2.5 A for 74% of tested complexes.     

Placement of medium-sized molecular fragments into active sites of proteins

Summary We present an algorithm for placing molecular fragments into the active site of a receptor. A molecular fragment is defined as a connected part of a molecule containing only complete ring systems. The algorithm is part of a docking tool, called FlexX, which is currently under development at GMD. The overall goal is to provide means of automatically computing low-energy conformations of the ligand within the active site, with an accuracy approaching the limitations of experimental methods for resolving molecular structures and within a run time that allows for docking large sets of ligands. The methods by which we plan to achieve this goal are the explicit exploitation of molecular flexibility of the ligand and the incorporation of physicochemical properties of the molecules. The algorithm for fragment placement, which is the topic of this paper, is based on pattern recognition techniques and is able to predict a small set of possible positions of a molecular fragment with low flexibility within seconds on a workstation. In most cases, a placement with rms deviation below 1.0 Å with respect to the X-ray structure is found among the 10 highest ranking solutions, assuming that the receptor is given in the bound conformation.     

Fully automated flexible docking of ligands into flexible synthetic receptors using forward and inverse docking strategies

The prediction of the structure of host-guest complexes is one of the most challenging problems in supramolecular chemistry. Usual procedures for docking of ligands into receptors do not take full conformational freedom of the host molecule into account. We describe and apply a new docking approach which performs a conformational sampling of the host and then sequentially docks the ligand into all receptor conformers using the incremental construction technique of the FlexX software platform. The applicability of this approach is validated on a set of host-guest complexes with known crystal structure. Moreover, we demonstrate that due to the interchangeability of the roles of host and guest, the docking process can be inverted. In this inverse docking mode, the receptor molecule is docked around its ligand. For all investigated test cases, the predicted structures are in good agreement with the experiment for both normal (forward) and inverse docking. Since the ligand is often smaller than the receptor and, thus, its conformational space is more restricted, the inverse docking approach leads in most cases to considerable speed-up. By having the choice between two alternative docking directions, the application range of the method is significantly extended. Finally, an important result of this study is the suitability of the simple energy function used here for structure prediction of complexes in organic media.     

TreeDock: a tool for protein docking based on minimizing van der Waals energies

Predicting protein-protein and protein-ligand docking remains one of the challenging topics of structural biology. The main problems are (i) to reliably estimate the binding free energies of docked states, (ii) to enumerate possible docking orientations at a high resolution, and (iii) to consider mobility of the docking surfaces and structural rearrangements upon interaction. Here we present a novel algorithm, TreeDock, that addresses the enumeration problem in a rigid-body docking search. By representing molecules as multidimensional binary search trees and by exploring a sufficient number of docking orientations such that two chosen atoms, one from each molecule, are always in contact, TreeDock is able to explore all clash-free orientations at very fine resolution in a reasonable amount of time. Due to the speed of the program, many contact pairs can be examined to search partial or complete surface areas. The deterministic systematic search of TreeDock is in contrast to most other docking programs that use stochastic searches such as Monte Carlo or simulated annealing methods. At this point, we have used the Lennard-Jones potential as the only scoring function and show that this can predict the correct docked conformation for a number of protein-protein and protein-ligand complexes. The program is most powerful if some information is known about the location of binding faces from NMR chemical-shift perturbation studies, orientation information from residual dipolar coupling, or mutational screening. The approach has the potential to include docking-site mobility by performing molecular dynamics or other randomization methods of the docking site and docking families to families of structures. The performance of the algorithm is demonstrated by docking three complexes of immunoglobulin superfamily domains, CD2 to CD58, the V(alpha) domain of a T-cell receptor to its V(beta) domain, and a T-cell receptor to a pMHC complex as well as a small molecule inhibitor to a phosphatase.     

Docking of ATP to Ca-ATPase: considering protein domain motions

Most standard molecular docking algorithms take into account only ligand flexibility, while numerous studies demonstrate that receptor flexibility may be also important. While some efficient methods have been proposed to take into account local flexibility of protein side chains, the influence of large-scale domain motions on the docking results still represents a challenge for computational methods. In this work we compared the results of ATP docking to different models of Ca-ATPase: crystallographic apo- and holo-forms of the enzyme as well as "flexible" target models generated via molecular dynamics (MD) simulations in water. MD simulations were performed for two different apo-forms and one holo-form of Ca2+-ATPase and reveal large-scale domain motions of type "closure", which is consistent with experimental structures. Docking to a set of MD-conformers yielded correct solutions with ATP bound in both domains regardless of the starting Ca2+-ATPase structure. Also, special attention was paid to proper ranking of docking solutions and some particular features of different scoring functions and their applicability for the model of "flexible" receptor. Particularly, the results of docking ATP were ranked by a scoring criterion specially designed to estimate ATP-protein interactions. This criterion includes stacking and hydrophobic interactions characteristic of ATP-protein complexes. The performance of this ligand-specific scoring function was considerably better than that of a standard scoring function used in the docking algorithm.     

Docking of small ligands to low-resolution and theoretically predicted receptor structures

We have developed a simple docking procedure that is able to utilize low-resolution models of proteins created by structure prediction algorithms such as threading or ab initio folding to predict the conformation of receptor-small ligand complexes. In our approach, using only approximate, discretized models of both molecules, we search for the steric and quasi-chemical complementarity between a ligand and the receptor molecules. This averaging procedure allows for the compensation of numerous structural inaccuracies resulting from the theoretical predictions of the receptor structure. The best relative orientation of these two models is obtained by an exhaustive scan over the rigid body's six-dimensional translational and rotational degrees of freedom. The search method is based on a real space grid-searching algorithm, unlike docking methods based on the fast Fourier Transform algorithm. We have applied this algorithm to rebuild structures of several complexes available in the Protein Data Bank. The structures of the receptors are produced by means of our threading algorithm PROSPECTOR, subsequently refined, and then utilized in the docking experiment. In many cases, not only is the localization of the binding site on the receptor surface correctly identified, but the proper orientation of the bounded ligand is also reasonably well reproduced within the level of accuracy of the modeled receptor itself.     

Efficient inclusion of receptor flexibility in grid-based protein-ligand docking

Accounting for receptor flexibility is an essential component of successful protein-ligand docking but still marks a major computational challenge. For many target molecules of pharmaceutical relevance, global backbone conformational changes are relevant during the ligand binding process. However, popular methods that represent the protein receptor molecule as a potential grid typically assume a rigid receptor structure during ligand-receptor docking. A new approach has been developed that combines inclusion of global receptor flexibility with the efficient potential grid representation of the receptor molecule. This is achieved using interpolation between grid representations of the receptor protein deformed in selected collective degrees of freedom. The method was tested on the docking of three ligands to apo protein kinase A (PKA), an enzyme that undergoes global structural changes upon inhibitor binding. Structural variants of PKA were generated along the softest normal mode of an elastic network representation of apo PKA. Inclusion of receptor deformability during docking resulted in a significantly improved docking performance compared with rigid PKA docking, thus allowing for systematic virtual screening applications at small additional computational cost.     

Immunoglobulin cross-reactivity examined by library screening, crystallography and docking studies

Antibodies are extremely diverse with respect to their specificities and affinities for target molecules. Despite rigorous selection, some antibodies are cross-reactive whereby they recognize their natural antigens along with other molecules. In this review, we discuss our efforts toward understanding the cross-reactivity of selected immunoglobulins. Investigations that are discussed employed screens of combinatorial peptide libraries, crystallography of ligand-protein complexes, and computer-based peptide docking simulations. In the first example, two different antibodies (NC6.8 and NC10.14) bound the same trisubstituted guanidine (NC174) with similar affinities, but utilized predominantly dissimilar binding strategies. However, there was one common binding strategy, in which the cyanophenyl portion of NC174 was inserted end-on into the binding crevices of the NC6.8 and NC10.14 antibodies. In the second example, scanning of peptide libraries and X-ray crystallography were used to design and test synthetic peptides for binding to the Mcg L chain dimer. Again, end-on insertion was favored for all peptides larger than dipeptides in the voluminous Mcg binding cavity. Finally, automated docking was used for rapid predictions of complexes for the Fv molecule from a broadly cross-reactive human IgM (Mez) and nearly two thousand peptides. Certain amino acids, including the aromatic residues Trp and Phe, functioned as anchoring groups in automated docking. Anchoring groups acted in most of the peptides that were otherwise accommodated by a variety of binding strategies in the docked complexes. We suggest that anchoring of at least a portion of a ligand in a binding site is a common mechanism for antibody recognition.     

A novel search engine for virtual screening of very large databases

Virtual screening of large chemical databases using the structure of the receptor can be computationally very demanding. We present a novel strategy that combines exhaustive similarity searches directly in SMILES format with the docking of flexible ligands, whose 3D structure is generated on the fly from the SMILES representation. Our strategy makes use of the recently developed LINGO tools to extract implicit chemical information from SMILES strings and integrates LINGO similarities into a pseudo-evolutionary algorithm. The algorithm represents a combination of a fast target-independent similarity method with a slower but information richer target-focused method. A virtual search of FactorXa ligands provided 62% of the potential hits after docking only 6.5% of a database of nearly 1 million molecules. The set of solutions showed good diversity, indicating that the method shows good scaffold hopping capabilities.     

An anchor-dependent molecular docking process for docking small flexible molecules into rigid protein receptors

A molecular docking method designated as ADDock, anchor- dependent molecular docking process for docking small flexible molecules into rigid protein receptors, is presented in this article. ADDock makes the bond connection lists for atoms based on anchors chosen for building molecular structures for docking small flexible molecules or ligands into rigid active sites of protein receptors. ADDock employs an extended version of piecewise linear potential for scoring the docked structures. Since no translational motion for small molecules is implemented during the docking process, ADDock searches the best docking result by systematically changing the anchors chosen, which are usually the single-edge connected nodes or terminal hydrogen atoms of ligands. ADDock takes intact ligand structures generated during the docking process for computing the docked scores; therefore, no energy minimization is required in the evaluation phase of docking. The docking accuracy by ADDock for 92 receptor-ligand complexes docked is 91.3%. All these complexes have been docked by other groups using other docking methods. The receptor-ligand steric interaction energies computed by ADDock for some sets of active and inactive compounds selected and docked into the same receptor active sites are apparently separated. These results show that based on the steric interaction energies computed between the docked structures and receptor active sites, ADDock is able to separate active from inactive compounds for both being docked into the same receptor.     

Fully automated molecular mechanics based induced fit protein-ligand docking method

We describe a method for docking a ligand into a protein receptor while allowing flexibility of the protein binding site. The method employs a multistep procedure that begins with the generation of protein and ligand conformations. An initial placement of the ligand is then performed by computing binding site hotspots. This initial placement is followed by a protein side-chain refinement stage that models protein flexibility. The final step of the process is an energy minimization of the ligand pose in the presence of the rigid receptor. Thus the algorithm models flexibility of the protein at two stages, before and after ligand placement. We validated this method by performing docking and cross docking studies of eight protein systems for which crystal structures were available for at least two bound ligands. The resulting rmsd values of the 21 docked protein-ligand complexes showed values of 2 A or less for all but one of the systems examined. The method has two critical benefits for high throughput virtual screening studies. First, no user intervention is required in the docking once the initial binding site selection has been made in the protein. Second, the initial protein conformation generation needs to be performed only once for a given binding region. Also, the method may be customized in various ways depending on the particular scenario in which dockings are being performed. Each of the individual steps of the method is fully independent making it straightforward to explore different variants of the high level workflow to further improve accuracy and performance.     

Automated flexible ligand docking method and its application for database search

We have developed a new docking program that explores ligand flexibility. This program can be applied to database searches. The program is similar in concept to earlier efforts, but it has been automated and improved. The algorithm begins by selecting an anchor fragment of a ligand. This fragment is protonated, as needed, and then placed in the receptor by the DOCK algorithm, followed by minimization using a simplex method. Finally, the conformations of the remaining parts of the putative ligands are searched by a limited backtrack method and minimized to get the most stable conformation. To test the efficiency of this method, the program was used to regenerate ten ligand–protein complex structures. In all cases, the docked ligands basically reproduced the crystallographic binding modes. The efficiency of this method was further tested by a database search. Ten percent of molecules from the Available Chemicals Directory (ACD) were docked to a dihydrofolate reductase structure. Most of the top-ranking molecules (7 of the top 13 hits) are dihydrofolate or methotrexate derivatives, which are known to be DHFR inhibitors, demonstrating the suitability of this program for screening molecular databases. © 1997 John Wiley & Sons, Inc. J Comput Chem 18 : 1812–1825, 1997     

Docking ligands into flexible and solvated macromolecules. 1. Development and validation of FITTED 1.0

We report the development and validation of a novel suite of programs, FITTED 1.0, for the docking of flexible ligands into flexible proteins. This docking tool is unique in that it can deal with both the flexibility of macromolecules (side chains and main chains) and the presence of bridging water molecules while treating protein/ligand complexes as realistically dynamic systems. This software relies on a genetic algorithm to account for the flexibility of the two molecules as well as the location of bridging water molecules. In addition, FITTED 1.0 features a novel application of a switching function to retain or displace key water molecules from the protein-ligand complexes. Two independent modules, ProCESS and SMART, were developed to set up the proteins and the ligands prior to the docking stage. Validation of the accuracy of the software was achieved via the application of FITTED 1.0 to the docking of inhibitors of HIV-1 protease, thymidine kinase, trypsin, factor Xa, and MMP to their respective proteins.     

MCDOCK: A Monte Carlo simulation approach to the molecular docking problem

Prediction of the binding mode of a ligand (a drug molecule) to its macromolecular receptor, or molecular docking, is an important problem in rational drug design. We have developed a new docking method in which a non-conventional Monte Carlo (MC) simulation technique is employed. A computer program, MCDOCK, was developed to carry out the molecular docking operation automatically. The current version of the MCDOCK program (version 1.0) allows for the full flexibility of ligands in the docking calculations. The scoring function used in MCDOCK is the sum of the interaction energy between the ligand and its receptor, and the conformational energy of the ligand. To validate the MCDOCK method, 19 small ligands, the binding modes of which had been determined experimentally using X-ray diffraction, were docked into their receptor binding sites. To produce statistically significant results, 20 MCDOCK runs were performed for each protein–ligand complex. It was found that a significant percentage of these MCDOCK runs converge to the experimentally observed binding mode. The root-mean-square (rms) of all non-hydrogen atoms of the ligand between the predicted and experimental binding modes ranges from 0.25 to 1.84 Å for these 19 cases. The computational time for each run on an SGI Indigo2/R10000 varies from less than 1 min to 15 min, depending upon the size and the flexibility of the ligands. Thus MCDOCK may be used to predict the precise binding mode of ligands in lead optimization and to discover novel lead compounds through structure-based database searching.     

Computer modeling of binding of diverse weak toxins to nicotinic acetylcholine receptors

Weak toxins are the "three-fingered" snake venoms toxins grouped together by having an additional disulfide in the N-terminal loop I. In general, weak toxins have low toxicity, and biological targets have been identified for some of them only, recently by detecting the effects on the nicotinic acetylcholine receptors (nAChR). Here the methods of docking and molecular dynamics simulations are used for comparative modeling of the complexes between four weak toxins of known spatial structure (WTX, candoxin, bucandin, gamma-bungarotoxin) and nAChRs. WTX and candoxin are those toxins whose blocking of the neuronal alpha7- and muscle-type nAChR has been earlier shown in binding assays and electrophysiological experiments, while for the other two toxins no such activity has been reported. Only candoxin and WTX are found here to give stable solutions for the toxin-nAChR complexes. These toxins appear to approach the binding site similarly to short alpha-neurotoxins, but their final position resembles that of alpha-cobratoxin, a long alpha-neurotoxin, in the complex with the acetylcholine-binding protein. The final spatial structures of candoxin and WTX complexes with the alpha7 neuronal or muscle-type nAChR are very similar and do not provide immediate answer why candoxin has a much higher affinity than WTX, but both of them share a virtually irreversible mode of binding to one or both these nAChR subtypes. Possible explanation comes from docking and MD simulations which predict fast kinetics of candoxin association with nAChR, no gross changes in the toxin conformation (with smaller toxin flexibility on alpha7 nAChR), while slow WTX binding to nAChR is associated with slow irreversible rearrangement both of the tip of the toxin loop II and of the binding pocket residues locking finally the toxin molecule. Computer modeling showed that the additional disulfide in the loop I is not directly involved in receptor binding of WTX and candoxin, but it stabilizes the structure of loop I which plays an important role in toxin delivery to the binding site. In summary, computer modeling visualized possible modes of binding for those weak toxins which interact with the nAChR, provided no solutions for those weak toxins whose targets are not the nAChRs, and demonstrated that the additional disulfide in loop I cannot be a sound criteria for joining all weak toxins into one group; the conclusion about the diversity of weak toxins made from computer modeling is in accord with the earlier phylogenetic analysis.