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     

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     

Refinement of NMR structures using implicit solvent and advanced sampling techniques

NMR biomolecular structure calculations exploit simulated annealing methods for conformational sampling and require a relatively high level of redundancy in the experimental restraints to determine quality three-dimensional structures. Recent advances in generalized Born (GB) implicit solvent models should make it possible to combine information from both experimental measurements and accurate empirical force fields to improve the quality of NMR-derived structures. In this paper, we study the influence of implicit solvent on the refinement of protein NMR structures and identify an optimal protocol of utilizing these improved force fields. To do so, we carry out structure refinement experiments for model proteins with published NMR structures using full NMR restraints and subsets of them. We also investigate the application of advanced sampling techniques to NMR structure refinement. Similar to the observations of Xia et al. (J.Biomol. NMR 2002, 22, 317-331), we find that the impact of implicit solvent is rather small when there is a sufficient number of experimental restraints (such as in the final stage of NMR structure determination), whether implicit solvent is used throughout the calculation or only in the final refinement step. The application of advanced sampling techniques also seems to have minimal impact in this case. However, when the experimental data are limited, we demonstrate that refinement with implicit solvent can substantially improve the quality of the structures. In particular, when combined with an advanced sampling technique, the replica exchange (REX) method, near-native structures can be rapidly moved toward the native basin. The REX method provides both enhanced sampling and automatic selection of the most native-like (lowest energy) structures. An optimal protocol based on our studies first generates an ensemble of initial structures that maximally satisfy the available experimental data with conventional NMR software using a simplified force field and then refines these structures with implicit solvent using the REX method. We systematically examine the reliability and efficacy of this protocol using four proteins of various sizes ranging from the 56-residue B1 domain of Streptococcal protein G to the 370-residue Maltose-binding protein. Significant improvement in the structures was observed in all cases when refinement was based on low-redundancy restraint data. The proposed protocol is anticipated to be particularly useful in early stages of NMR structure determination where a reliable estimate of the native fold from limited data can significantly expedite the overall process. This refinement procedure is also expected to be useful when redundant experimental data are not readily available, such as for large multidomain biomolecules and in solid-state NMR structure determination.     

Flexible protein‐ligand docking using the Fleksy protocol

Considering protein plasticity is important in accurately predicting the three‐dimensional geometry of protein‐ligand complexes. Here, we present the first public release of our flexible docking tool Fleksy, which is able to consider both ligand and protein flexibility in the docking process. We describe the workflow and different features of the software and present its performance on two cross‐docking benchmark datasets. © 2012 Wiley Periodicals, Inc.     

Mechanism of ligand exchange studied using transition path sampling

The mechanism of intermolecular ligand exchange has been studied using transition path sampling (TPS) based molecular dynamics (MD) simulations. Specifically, the exchange of solvent molecules bound to unsaturated Cr(CO)5 in methanol solution has been investigated. The results of the TPS simulations have shown that there are multiple steps in the reaction mechanism. The first involves partial dissociation of the coordinated solvent from the Cr metal center followed by association with a new methanol molecule between the normally void first and second solvent layers. After diffusive motion of the exchanging ligands, the last step involves the originally bound methanol molecule moving into the bath continuum followed by solvation of the Cr metal fragment by the exchanging ligand. It has been found that the reaction center (defined as the organometallic fragment and two exchanging ligands only) and the solvent bath have favorable interactions. This is likely due to the adiabatic nature of the ligand exchange transition. The ability to understand the microscopic molecular dynamics of a chemical process based on a free energy analysis is also discussed.     

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).     

Pre-binding dynamic range and sensitivity enhancement for immuno-sensors using nanofluidic preconcentrator

Almost all immuno-biosensors are inherently limited by the quality of antibodies available for the target molecule, and obtaining a highly sensitive antibody for a given target molecule is a challenge. We describe a highly efficient and flexible way to enhance immunoassay detection sensitivity and binding kinetics using a nanofluidic based electrokinetic preconcentrator. The device is a microfluidic integration of charge-based biomolecule concentrator and a bead-based immunoassay. Because the preconcentrator can increase the local biomolecule concentration by many orders of magnitude, it gives the immuno-sensor better sensitivity and faster binding kinetics. With a 30 min preconcentration, we were able to enhance the immunoassay sensitivity (with molecular background) by more than 500 fold from higher 50 pM to the sub 100 fM range. Moreover, by adjusting the preconcentration time, we can switch the detection range of the given bead-based assay (from 10-10 000 ng ml(-1) to 0.01-10 000 ng ml(-1)) to have a broader dynamic range of detection. As the system can enhance both detection sensitivity and dynamic range, it can be used to address the most critical detection issues in the detection of common disease biomarkers.     

Simultaneous enantioseparation and sensitivity enhancement of basic drugs using large-volume sample stacking

Simultaneous enantioseparation with sensitive detection of four basic drugs, namely methoxamine, metaproterenol, terbutaline and carvedilol, using a 20-mum ID capillary with native beta-CD as the chiral selector was demonstrated by the large-volume sample stacking method. The procedure included conventional sample loading either hydrodynamically or electrokinetically at longer injection times without polarity switching and EOF manipulation. In comparison to conventional injections, depending on the analyte, about several hundred- and a thousand-fold sensitivity enhancement was achieved with the hydrodynamic and the electrokinetic injections, respectively. The simple method developed was applied to the analysis of racemic analytes in serum samples and better recovery was achieved using hydrodynamic injection than electrokinetic injection.     

Prediction of binding poses to FXR using multi-targeted docking combined with molecular dynamics and enhanced sampling

Advanced molecular docking methods often aim at capturing the flexibility of the protein upon binding to the ligand. In this study, we investigate whether instead a simple rigid docking method can be applied, if combined with multiple target structures to model the backbone flexibility and molecular dynamics simulations to model the sidechain and ligand flexibility. The methods are tested for the binding of 35 ligands to FXR as part of the first stage of the Drug Design Data Resource (D3R) Grand Challenge 2 blind challenge. The results show that the multiple-target docking protocol performs surprisingly well, with correct poses found for 21 of the ligands. MD simulations started on the docked structures are remarkably stable, but show almost no tendency of refining the structure closer to the experimentally found binding pose. Reconnaissance metadynamics enhances the exploration of new binding poses, but additional collective variables involving the protein are needed to exploit the full potential of the method.     

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.     

A new peptide docking strategy using a mean field technique with mutually orthogonal Latin square sampling

The theoretical prediction of the association of a flexible ligand with a protein receptor requires efficient sampling of the conformational space of the ligand. Several docking methodologies are currently available. We propose a new docking technique that performs well at low computational cost. The method uses mutually orthogonal Latin squares to efficiently sample the docking space. A variant of the mean field technique is used to analyze this sample to arrive at the optimum. The method has been previously applied to explore the conformational space of peptides and identify structures with low values for the potential energy. Here we extend this method to simultaneously identify both the low energy conformation as well as a ‘high-scoring’ docking mode. Application of the method to 56 protein–peptide complexes, in which the length of the peptide ligand ranges from three to seven residues, and comparisons with Autodock 3.05, showed that the method works well. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Dramatic enhancement of enantioselectivity of biotransformations of beta-hydroxy nitriles using a simple O-benzyl protection/docking group

[Structure: see text] Catalyzed by the Rhodococcus erythropolis AJ270 whole cell catalyst, the O-benzylated beta-hydroxy alkanenitriles underwent remarkably high enantioselective biotransformations, whereas the biotransformations of free beta-hydroxy alkanenitriles gave very low enantioselectivity. The easy manipulations of O-protection and O-deprotection, excellent chemical and enantiomeric yields of biotransformations, along with the scalability render this enzymatic transformation attractive and practical for the synthesis of highly enantiopure beta-hydroxy alkanoic acids and their amide derivatives.     

GalaxyDock2: Protein–ligand docking using beta‐complex and global optimization

In this article, an enhanced version of GalaxyDock protein–ligand docking program is introduced. GalaxyDock performs conformational space annealing (CSA) global optimization to find the optimal binding pose of a ligand both in the rigid‐receptor mode and the flexible‐receptor mode. Binding pose prediction has been improved compared to the earlier version by the efficient generation of high‐quality initial conformations for CSA using a predocking method based on a beta‐complex derived from the Voronoi diagram of receptor atoms. Binding affinity prediction has also been enhanced by using the optimal combination of energy components, while taking into consideration the energy of the unbound ligand state. The new version has been tested in terms of binding mode prediction, binding affinity prediction, and virtual screening on several benchmark sets, showing improved performance over the previous version and AutoDock, on which the GalaxyDock energy function is based. GalaxyDock2 also performs better than or comparable to other state‐of‐the‐art docking programs. GalaxyDock2 is freely available at http://galaxy.seoklab.org/softwares/galaxydock.html . © 2013 Wiley Periodicals, Inc.     

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.     

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.     

Representing receptor flexibility in ligand docking through relevant normal modes

Inspired by the current representation of the ligand-receptor binding process, a normal-mode-based methodology is presented to incorporate receptor flexibility in ligand docking and virtual screening. However, the systematic representation of the deformation space grows geometrically with the number of modes, and furthermore, midscale loop rearrangements like those found in protein kinase binding pockets cannot be accounted for with the first lowest-frequency modes. We thus introduced a measure of relevance of normal modes on a given region of interest and showed that only very few modes in the low-frequency range are necessary and sufficient to describe loop flexibility in cAMP-dependent protein kinase. We used this approach to generate an ensemble of representative receptor backbone conformations by perturbing the structure along a combination of relevant modes. Each ensemble conformation is complexed with known non-native binders to optimize the position of the binding-pocket side chains through a full flexible docking procedure. The multiple receptor conformations thus obtained are used in a small-scale virtual screening using receptor ensemble docking. We evaluated this algorithm on holo and apo structures of cAMP-dependent protein kinase that exhibit backbone rearrangements on two independent loop regions close to the binding pocket. Docking accuracy is improved, since the ligands considered in the virtual screening docked within 1.5 A to at least one of the structures. The discrimination between binders and nonbinders is also enhanced, as shown by the improvement of the enrichment factor. This constitutes a new step toward the systematic integration of flexible ligand-flexible receptor docking tools in structure-based drug discovery.     

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.     

Bioactivity and molecular docking of synthesized macromolecular ligand and its complex

The development of drug resistant strains of the pathogenic fungi despite the availability of large number of drugs demands the development of new and more potential drug molecules. Dendrimer based drug molecules are comparatively less researched upon and a recent advancement in this field. The present study is concerned with the preparation of macromolecular ligand and its complex using ethylenediamine and methylmethacrylate as starting material. The reaction goes via Michael addition reaction and synthesized dendritic units were used as ligands to obtain metal-ligand complexes. Obtained ligand and its complex were characterized in terms of different techniques such as FTIR, ¹H NMR, ESI-MS, UV–Vis and Elemental analysis. Further, the ligand and its complex were used to determine antifungal activity against C. albicans ATCC 90028 by MICs and Disk diffusion assay. Comet assay and Molecular docking techniques were used to show toxicity effects and ligand–DNA interactions respectively. Ligand and its complex were obtained in very good yield with square planar geometry and having good antifungal potential against C. albicans. It was also found from Molecular docking and Comet assay, that the Copper complex interacts strongly with DNA and shows less toxicity than ligand. The compounds can serve as promising leads for the development of new antifungal agents.