Ligand-protein docking with water molecules

The presence of water molecules plays an important role in the accuracy of ligand-protein docking predictions. Comprehensive docking simulations have been performed on a large set of ligand-protein complexes whose crystal structures contain water molecules in their binding sites. Only those water molecules found in the immediate vicinity of both the ligand and the protein were considered. We have investigated whether prior optimization of the orientation of water molecules in either the presence or absence of the bound ligand has any effect on the accuracy of docking predictions. We have observed a statistically significant overall increase in accuracy when water molecules are included during docking simulations and have found this to be independent of the method of optimization of the orientation of water molecules. These results confirm the importance of including water molecules whenever possible in a ligand-protein docking simulation. Our findings also reveal that prior optimization of the orientation of water molecules, in the absence of any bound ligand, does not have a detrimental effect on the improved accuracy of ligand-protein docking. This is important, given the use of docking simulations to predict the binding modes of new ligands or drug molecules.     

Behavior of water molecules near monolayer-protected clusters with different terminal segments of ligand

Molecular dynamics simulations are performed to investigate the behavior of water molecules near gold monolayer protected clusters (MPCs) with two different types of surfactant, HS(CH(2))(5)(OCH(2)CH(2))(2)COOH (type1) and HS(CH(2))(11)COOH (type2). The effects of the different moieties of the two ligands on the local structure of the water molecules are quantified by means of the reduced density profiles of oxygen and hydrogen atoms, and the hydrogen bond statistics. The adsorption characteristics of water molecules are evaluated by means of their residence time near the MPCs. The results show that the hydrophilic oligo (ethylene glycol) segment increases the number of water molecules, which penetrate the protective layer of MPC. As a result, the inter-water hydrogen bond network in the protective layer of type1 MPC is stronger than that in the protective layer of the type2 MPC. It is shown that the presence of interfacial hydrogen bonds increases the adsorption of water molecules near the MPCs and therefore constrains the motion of MPCs. As a result, the residence time of the water molecules adjacent to the type1 MPC is longer than that of the molecules adjacent to the type2 MPC.     

Comparing ligand interactions with multiple receptors via serial docking

Standard uses of ligand-receptor docking typically focus on the association of candidate ligands with a single targeted receptor, but actual applications increasingly require comparisons across multiple receptors. This study demonstrates that comparative docking to multiple receptors can help to select homology models for virtual compound screening and to discover ligands that bind to one set of receptors but not to another, potentially similar, set. A serial docking algorithm is furthermore described that reduces the computational costs of such calculations by testing compounds against a series of receptor structures and discarding a compound as soon as it fails to satisfy specified bind/no bind criteria for each receptor. The algorithm also realizes substantial efficiencies by taking advantage of the fact that a ligand typically binds in similar conformations to similar receptors. Thus, once detailed docking has been used to fit a ligand into the first of a series of similar receptors, much less extensive calculations can be used for the remaining structures.     

De novo ligand design with explicit water molecules: an application to bacterial neuraminidase

Most computer-aided drug design methods ignore the presence of crystallographically-determined water molecules in the binding site of a target protein. In this paper, our de novo ligand design methods are applied to the X-ray crystal structure of bacterial neuraminidase in the presence of some selected water molecules. We have found that, for this particular protein, the complete removal of all bound water molecules leads to difficulties in generating any potential ligands if the unsatisfied hydrogen-bonding sitepoints left by removing these water molecules are to be satisfied by a ligand. As more of the crystallographically determined water molecules are allowed in the binding site, it becomes much easier to generate ligands in larger numbers and with wider chemical diversity. This example shows that, in some cases, bound water molecules can be more accessible for hydrogen bonding to an incoming ligand than the actual protein binding sitepoints associated with them. From the point of view of de novo ligand design, water molecules can thus act as versatile amphiprotic hydrogen-bonding sitepoints and reduce the conformational constraints of a particular binding site.     

Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets

The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.     

Q-Dock: Low-resolution flexible ligand docking with pocket-specific threading restraints

The rapidly growing number of theoretically predicted protein structures requires robust methods that can utilize low-quality receptor structures as targets for ligand docking. Typically, docking accuracy falls off dramatically when apo or modeled receptors are used in docking experiments. Low-resolution ligand docking techniques have been developed to deal with structural inaccuracies in predicted receptor models. In this spirit, we describe the development and optimization of a knowledge-based potential implemented in Q-Dock, a low-resolution flexible ligand docking approach. Self-docking experiments using crystal structures reveals satisfactory accuracy, comparable with all-atom docking. All-atom models reconstructed from Q-Dock's low-resolution models can be further refined by even a simple all-atom energy minimization. In decoy-docking against distorted receptor models with a root-mean-square deviation, RMSD, from native of approximately 3 A, Q-Dock recovers on average 15-20% more specific contacts and 25-35% more binding residues than all-atom methods. To further improve docking accuracy against low-quality protein models, we propose a pocket-specific protein-ligand interaction potential derived from weakly homologous threading holo-templates. The success rate of Q-Dock employing a pocket-specific potential is 6.3 times higher than that previously reported for the Dolores method, another low-resolution docking approach.     

Flexible ligand docking using a genetic algorithm

Summary Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.Abbreviations GA genetic algorithm; dhfr, dihydrofolate reductase - mtx methotrexate - ts thymidylate synthase - fen phenolphalein - HIV human immune deficiency virus - hivp HIV protease - thk thioketal haloperidol     

Molecular dynamics investigation of bent-core molecules on a water surface

Molecular dynamics simulations are carried out for bent-core molecules at water surfaces. The water surface is shown to alter the equilibrium molecular structure significantly by causing a different class of torsional states to become more favorable. The equilibrium structure is also altered by the substitution of chlorine atoms for hydrogen atoms on the central phenyl ring in that this substitution forces the bent core to remain in a single torsional state rather than be delocalized among several torsional states. The consequences of these structural changes on the chirality and packing of these molecules on water surfaces are discussed.     

Molecular docking using shape descriptors

Molecular docking explores the binding modes of two interacting molecules. The technique is increasingly popular for studying protein-ligand interactions and for drug design. A fundamental problem problem with molecular docking is that orientation space is very large and grows combinatorially with the number of degrees of freedom of the interacting molecules. Here, we describe and evaluate algorithms that improve the efficiency and accuracy of a shape-based docking method. We use molecular organization and sampling techniques to remove the exponential time dependence on molecular size in docking calculations. The new techniques allow us to study systems that were prohibitively large for the original method. The new algorithms are tested in 10 different protein-ligand systems, including 7 systems where the ligand is itself a protein. In all cases, the new algorithms successfully reproduce the experimentally determined configurations of the ligand in the protein.     

Flexible ligand docking using a robust evolutionary algorithm

A flexible ligand docking protocol based on evolutionary algorithms is investigated. The proposed approach incorporates family competition and adaptive rules to integrate decreasing‐based mutations and self‐adaptive mutations to act as global and local search strategies, respectively. The method is applied to a dihydrofolate reductase enzyme with the anticancer drug methotrexate and two analogues of antibacterial drug trimethoprim. Conformations and orientations closed to the crystallographically determined structures are obtained, as well as alternative structures with low energy. Numerical results indicate that the new approach is very robust. The docked lowest‐energy structures have root‐mean‐square derivations ranging from 0.67 to 1.96 Å with respect to the corresponding crystal structures. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 988–998, 2000     

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.     

Significant enhancement of docking sensitivity using implicit ligand sampling

The efficient and accurate quantification of protein-ligand interactions using computational methods is still a challenging task. Two factors strongly contribute to the failure of docking methods to predict free energies of binding accurately: the insufficient incorporation of protein flexibility coupled to ligand binding and the neglected dynamics of the protein-ligand complex in current scoring schemes. We have developed a new methodology, named the 'ligand-model' concept, to sample protein conformations that are relevant for binding structurally diverse sets of ligands. In the ligand-model concept, molecular-dynamics (MD) simulations are performed with a virtual ligand, represented by a collection of functional groups that binds to the protein and dynamically changes its shape and properties during the simulation. The ligand model essentially represents a large ensemble of different chemical species binding to the same target protein. Representative protein structures were obtained from the MD simulation, and docking was performed into this ensemble of protein conformation. Similar binding poses were clustered, and the averaged score was utilized to rerank the poses. We demonstrate that the ligand-model approach yields significant improvements in predicting native-like binding poses and quantifying binding affinities compared to static docking and ensemble docking simulations into protein structures generated from an apo MD simulation.     

Comparative study of several algorithms for flexible ligand docking

We have performed a comparative assessment of several programs for flexible molecular docking: DOCK 4.0, FlexX 1.8, AutoDock 3.0, GOLD 1.2 and ICM 2.8. This was accomplished using two different studies: docking experiments on a data set of 37 protein-ligand complexes and screening a library containing 10,037 entries against 11 different proteins. The docking accuracy of the methods was judged based on the corresponding rank-one solutions. We have found that the fraction of molecules docked with acceptable accuracy is 0.47, 0.31, 0.35, 0.52 and 0.93 for, respectively, AutoDock, DOCK, FlexX, GOLD and ICM. Thus ICM provided the highest accuracy in ligand docking against these receptors. The results from the other programs are found to be less accurate and of approximately the same quality. A speed comparison demonstrated that FlexX was the fastest and AutoDock was the slowest among the tested docking programs. The database screening was performed using DOCK, FlexX and ICM. ICM was able to identify the original ligands within the top 1% of the total library in 17 cases. The corresponding number for DOCK and FlexX was 7 and 8, respectively. We have estimated that in virtual database screening, 50% of the potentially active compounds will be found among approximately 1.5% of the top scoring solutions found with ICM and among approximately 9% of the top scoring solutions produced by DOCK and FlexX.     

表皮生长因子受体和抑制剂之间分子对接的研究

研究了表皮生长因子受体(EGFR)和4-苯胺喹唑啉类抑制剂之间的相互作用模式，表皮生长因子受体的三维结构通过同源蛋白模建的方法得到，而抑制剂和靶酶结合复合物结构则通过分子力学和分子动力学结合的方法计算得到。从模拟结果得到的抑制剂和靶酶之间的相互作用模式表明范德华相互作用、疏水相互作用以及氢键相互作用对抑制剂的活性都有重要的影响，抑制剂的苯胺部分位于活性口袋的底部，能够与受体残基的非极性侧链产生很强的范德华和疏水相互作用，抑制剂双环上的取代基团也能和活性口袋外部的部分残基形成一定的范德华和疏水性相互作用，而抑制剂喹唑啉环上的氮原子能和周围的残基形成较强的氢键相互作用，对抑制剂的活性有较大的影响，计算得到抑制剂和靶酶之间的非键相互作用能以及抑制剂和靶酶之间的相互作用信息能够很好地解释抑制剂活性和结构的关系，为全新抑制剂的设计提供了重要的结构信息。     

Exploring hierarchical refinement techniques for induced fit docking with protein and ligand flexibility

We present a series of molecular‐mechanics‐based protein refinement methods, including two novel ones, applied as part of an induced fit docking procedure. The methods used include minimization; protein and ligand sidechain prediction; a hierarchical ligand placement procedure similar to a‐priori protein loop predictions; and a minimized Monte Carlo approach using normal mode analysis as a move step. The results clearly indicate the importance of a proper opening of the active site backbone, which might not be accomplished when the ligand degrees of freedom are prioritized. The most accurate method consisted of the minimized Monte Carlo procedure designed to open the active site followed by a hierarchical optimization of the sidechain packing around a mobile flexible ligand. The methods have been used on a series of 88 protein‐ligand complexes including both cross‐docking and apo‐docking members resulting in complex conformations determined to within 2.0 Å heavy‐atom RMSD in 75% of cases where the protein backbone rearrangement upon binding is less than 1.0 Å α‐carbon RMSD. We also demonstrate that physics‐based all‐atom potentials can be more accurate than docking‐style potentials when complexes are sufficiently refined. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Enantioselective crystal growth of leucine on a self-assembled monolayer with covalently attached leucine molecules

Enantioselective crystal growth of leucine occurs on a solid surface modified with a self-assembled monolayer depending on the chirality of the enantiomer attached, as evidenced by the X-ray diffraction method.     

Computational simulation of ligand docking to L-type pyruvate kinase subunit

Computational blind docking approach was used for mapping of possible binding sites in L-type pyruvate kinase subunit for peptides, RRASVA and the phosphorylated derivative RRAS(P_i)VA, which model the phosphorylatable N-terminal regulatory domain of the enzyme. In parallel, the same docking analysis was done for both substrates of this enzyme, phosphoenolpyruvate (PEP) and adenosine diphosphate (ADP), and for docking of fructose 1,6-bisphosphate (FBP), which is the allosteric activator of the enzyme. The binding properties of the entire surface of the protein were scanned and several possible binding sites were identified in domains A and C of the protein, while domain B revealed no docking sites for peptides or for substrates or the allosteric regulator. It was found that the docking sites of different ligands were partially overlapping, pointing to the possibility that some regulatory effects, observed in the case of L-type pyruvate kinase, may be caused by the competition of different ligands for the same binding sites.     

Rational design of affinity peptide ligand by flexible docking simulation

Rational design of affinity peptide ligands of proteins by flexible docking simulation is performed using the SYBYL program package. This approach involves the use of experimental data to verify a scoring function that can be used to assess the affinity of a peptide for its target protein. The enzyme-linked immunosorbent assay (ELISA) data of several peptides displayed on phage surfaces for insulin and lysozyme, respectively, reported in literature are used for the purpose. It is found that the absolute values of the Dscore calculated from the docking correspond well to the ELISA data that relate to the affinity between the peptides and the target molecule. So, the Dscore function is used to assess the affinity of docked peptides in a pentapeptide library designed on the basis of protein (alpha-amylase) structure. As a result, a pentapeptide with a high Dscore value is selected and a hexapeptide (FHENWS) is built by linking serine to its C-terminal to lengthen the peptide. Molecular surface analysis with the MOLCAD program reveals that electrostatic interactions (including hydrogen bonds) and Van der Waals forces contribute to the affinity of the hexapeptide for alpha-amylase. Chromatographic experiments with the immobilized peptide have given further evidence for this observation. Adsorption isotherm described by the Langmuir equation indicates that the apparent binding constant of alpha-amylase to the immobilized hexapeptide was 2.5x10(5)L/mol. Finally, high affinity and specificity of the affinity adsorbent is exemplified by the purification of alpha-amylase from crude fermentation broth of Bacillus subtilis.