Showing papers on "Docking (molecular) published in 2008"

Recent progress and future directions in protein-protein docking.

Abstract: This article gives an overview of recent progress in protein-protein docking and it identifies several directions for future research. Recent results from the CAPRI blind docking experiments show that docking algorithms are steadily improving in both reliability and accuracy. Current docking algorithms employ a range of efficient search and scoring strategies, including e.g. fast Fourier transform correlations, geometric hashing, and Monte Carlo techniques. These approaches can often produce a relatively small list of up to a few thousand orientations, amongst which a near-native binding mode is often observed. However, despite the use of improved scoring functions which typically include models of desolvation, hydrophobicity, and electrostatics, current algorithms still have difficulty in identifying the correct solution from the list of false positives, or decoys. Nonetheless, significant progress is being made through better use of bioinformatics, biochemical, and biophysical information such as e.g. sequence conservation analysis, protein interaction databases, alanine scanning, and NMR residual dipolar coupling restraints to help identify key binding residues. Promising new approaches to incorporate models of protein flexibility during docking are being developed, including the use of molecular dynamics snapshots, rotameric and off-rotamer searches, internal coordinate mechanics, and principal component analysis based techniques. Some investigators now use explicit solvent models in their docking protocols. Many of these approaches can be computationally intensive, although new silicon chip technologies such as programmable graphics processor units are beginning to offer competitive alternatives to conventional high performance computer systems. As cryo-EM techniques improve apace, docking NMR and X-ray protein structures into low resolution EM density maps is helping to bridge the resolution gap between these complementary techniques. The use of symmetry and fragment assembly constraints are also helping to make possible docking-based predictions of large multimeric protein complexes. In the near future, the closer integration of docking algorithms with protein interface prediction software, structural databases, and sequence analysis techniques should help produce better predictions of protein interaction networks and more accurate structural models of the fundamental molecular interactions within the cell.

Principles of Flexible Protein-Protein Docking

Abstract: Treating flexibility in molecular docking is a major challenge in cell biology research. Here we describe the background and the principles of existing flexible protein-protein docking methods, focusing on the algorithms and their rational. We describe how protein flexibility is treated in different stages of the docking process: in the preprocessing stage, rigid and flexible parts are identified and their possible conformations are modeled. This preprocessing provides information for the subsequent docking and refinement stages. In the docking stage, an ensemble of pre-generated conformations or the identified rigid domains may be docked separately. In the refinement stage, small-scale movements of the backbone and side-chains are modeled and the binding orientation is improved by rigid-body adjustments. For clarity of presentation, we divide the different methods into categories. This should allow the reader to focus on the most suitable method for a particular docking problem.

Molecular Interactions of CCR5 with Major Classes of Small-Molecule Anti-HIV CCR5 Antagonists

Abstract: In addition to being an important receptor in leukocyte activation and mobilization, CCR5 is the essential coreceptor for human immunodeficiency virus (HIV). A large number of small-molecule CCR5 antagonists have been reported that show potent activities in blocking chemokine function and HIV entry. To facilitate the design and development of next generation CCR5 antagonists, docking models for major classes of CCR5 antagonists were created by using site-directed mutagenesis and CCR5 homology modeling. Five clinical candidates: maraviroc, vicriviroc, aplaviroc, TAK-779, and TAK-220 were used to establish the nature of the binding pocket in CCR5. Although the five antagonists are very different in structure, shape, and electrostatic potential, they were able to fit in the same binding pocket formed by the transmembrane (TM) domains of CCR5. It is noteworthy that each antagonist displayed a unique interaction profile with amino acids lining the pocket. Except for TAK-779, all antagonists showed strong interaction with Glu283 in TM 7 via their central basic nitrogen. The fully mapped binding pocket of CCR5 is being used for structure-based design and lead optimization of novel anti-HIV CCR5 inhibitors with improved potency and better resistance profile.

Molecular docking of intercalators and groove-binders to nucleic acids using Autodock and Surflex.

Abstract: The molecular docking tools Autodock and Surflex accurately reproduce the crystallographic structures of a collection of small molecule ligands that have been shown to bind nucleic acids. Docking studies were performed with the intercalators daunorubicin and ellipticine and the minor groove binders distamycin and pentamidine. Autodock and Surflex dock daunorubicin and distamycin to their nucleic acid targets within a resolution of approximately 2 A, which is similar to the limit of the crystal structure resolution. However, for the top ranked poses, Autodock and Surflex both dock ellipticine into the correct site but in a different orientation compared to the crystal structure. This appears not only to be partly related to the symmetry of the target nucleic acid, as ellipticine is able to dock from either side of the intercalation site, but also due to the shape of the ligand and docking accuracy. Surflex docks pentamidine in a symmetrically equivalent orientation relative to the crystal structure, while Autodock was able to dock this molecule in the original orientation. In the case of the Surflex docking of pentamidine, the initial rmsd is misleading, given the symmetrical structure of pentamidine. Importantly, the ranking functions of both of these programs are able to return a top pose within approximately 2 A rmsd for daunorubicin, distamycin, and pentamidine and approximately 3 A rmsd for ellipticine compared to their respective crystal structures. Some docking challenges and potential pitfalls are explored, such as the importance of hydrogen treatment on ligands as well as the scoring functions of Autodock and Surflex. Overall for this set of complexes, Surflex is preferred over Autodock for virtual screening, as although the results are comparable, Surflex has significantly faster performance and ease of use under the optimal software conditions tested. These experiments show that molecular docking techniques can be successfully extended to include nucleic acid targets, a finding which has important implications for virtual screening applications and in the design of new small molecules to target therapeutically relevant morphologies of nucleic acids.

Affinity maturation of antibodies assisted by in silico modeling

Abstract: Rational engineering methods can be applied with reasonable success to optimize physicochemical characteristics of proteins, in particular, antibodies. Here, we describe a combined CDR3 walking randomization and rational design-based approach to enhance the affinity of the human anti-gastrin TA4 scFv. The application of this methodology to TA4 scFv, displaying only a weak overall affinity for gastrin17 (KD = 6 μM), resulted in a set of nine affinity-matured scFv variants with near-nanomolar affinity (KD = 13.2 nM for scFv TA4.112). First, CDR-H3 and CDR-L3 randomization resulted in three scFvs with an overall affinity improvement of 15- to 35-fold over the parental. Then, the modeling of two scFv constructs selected from the previous step (TA4.11 and TA4.13) was followed by a combination of manual and molecular dynamics-based docking of gastrin17 into the respective binding sites, analysis of apparent packing defects, and selection of residues for mutagenesis through phage display. Nine scFv mutants were obtained from the second maturation step. A final 454-fold improvement in affinity compared with TA4 was obtained. These scFvs showed an enhanced potency to inhibit gastrin-induced proliferation in Colo 320 WT and BxPc3 tumoral cells. In conclusion, we propose a structure-based rational method to accelerate the development of affinity-matured antibody constructs with enhanced potential for therapeutic use.

MedusaScore: an accurate force field-based scoring function for virtual drug screening.

Abstract: Virtual screening is becoming an important tool for drug discovery. However, the application of virtual screening has been limited by the lack of accurate scoring functions. Here, we present a novel scoring function, MedusaScore, for evaluating protein-ligand binding. MedusaScore is based on models of physical interactions that include van der Waals, solvation, and hydrogen bonding energies. To ensure the best transferability of the scoring function, we do not use any protein-ligand experimental data for parameter training. We then test the MedusaScore for docking decoy recognition and binding affinity prediction and find superior performance compared to other widely used scoring functions. Statistical analysis indicates that one source of inaccuracy of MedusaScore may arise from the unaccounted entropic loss upon ligand binding, which suggests avenues of approach for further MedusaScore improvement.

Structure of Epac2 in complex with a cyclic AMP analogue and RAP1B

Abstract: Epac proteins are activated by binding of the second messenger cAMP and then act as guanine nucleotide exchange factors for Rap proteins. The Epac proteins are involved in the regulation of cell adhesion and insulin secretion. Here we have determined the structure of Epac2 in complex with a cAMP analogue (Sp-cAMPS) and RAP1B by X-ray crystallography and single particle electron microscopy. The structure represents the cAMP activated state of the Epac2 protein with the RAP1B protein trapped in the course of the exchange reaction. Comparison with the inactive conformation reveals that cAMP binding causes conformational changes that allow the cyclic nucleotide binding domain to swing from a position blocking the Rap binding site towards a docking site at the Ras exchange motif domain.

Discovery of Novel Chemotypes to a G-Protein-Coupled Receptor through Ligand-Steered Homology Modeling and Structure-Based Virtual Screening

Abstract: Melanin-concentrating hormone receptor 1 (MCH-R1) is a G-protein-coupled receptor (GPCR) and a target for the development of therapeutics for obesity. The structure-based development of MCH-R1 and other GPCR antagonists is hampered by the lack of an available experimentally determined atomic structure. A ligand-steered homology modeling approach has been developed (where information about existing ligands is used explicitly to shape and optimize the binding site) followed by docking-based virtual screening. Top scoring compounds identified virtually were tested experimentally in an MCH-R1 competitive binding assay, and six novel chemotypes as low micromolar affinity antagonist "hits" were identified. This success rate is more than a 10-fold improvement over random high-throughput screening, which supports our ligand-steered method. Clearly, the ligand-steered homology modeling method reduces the uncertainty of structure modeling for difficult targets like GPCRs.

Molecular docking algorithms.

Abstract: By means of virtual screening of small molecules databases it is possible to identify new potential inhibitors against a target of interest Molecular docking is a computer simulation procedure to predict the conformation of a receptor-ligand complex Each docking program makes use of one or more specific search algorithms, which are the methods used to predict the possible conformations of a binary complex In the present review we describe several molecular-docking search algorithms, and the programs which apply such methodologies We also discuss how virtual screening can be optimized, describing methods that may increase accuracy of the simulation process, with relatively fast docking algorithms

Lead finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening.

Abstract: An innovative molecular docking algorithm and three specialized high accuracy scoring functions are introduced in the Lead Finder docking software. Lead Finder’s algorithm for ligand docking combines the classical genetic algorithm with various local optimization procedures and resourceful exploitation of the knowledge generated during docking process. Lead Finder’s scoring functions are based on a molecular mechanics functional which explicitly accounts for different types of energy contributions scaled with empiric coefficients to produce three scoring functions tailored for (a) accurate binding energy predictions; (b) correct energy-ranking of docked ligand poses; and (c) correct rank-ordering of active and inactive compounds in virtual screening experiments. The predicted values of the free energy of protein−ligand binding were benchmarked against a set of experimentally measured binding energies for 330 diverse protein−ligand complexes yielding rmsd of 1.50 kcal/mol. The accuracy of ligand docking wa...

Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase

Abstract: High-throughput screening (HTS) is widely used in drug discovery Especially for screens of unbiased libraries, false positives can dominate “hit lists”; their origins are much debated Here we determine the mechanism of every active hit from a screen of 70,563 unbiased molecules against β-lactamase using quantitative HTS (qHTS) Of the 1274 initial inhibitors, 95% were detergent-sensitive and were classified as aggregators Among the 70 remaining were 25 potent, covalent-acting β-lactams Mass spectra, counter-screens, and crystallography identified 12 as promiscuous covalent inhibitors The remaining 33 were either aggregators or irreproducible No specific reversible inhibitors were found We turned to molecular docking to prioritize molecules from the same library for testing at higher concentrations Of 16 tested, 2 were modest inhibitors Subsequent X-ray structures corresponded to the docking prediction Analog synthesis improved affinity to 8 µM These results suggest that it may be the physical b

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

Abstract: 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 virt...

Investigations on the 4-quinolone-3-carboxylic acid motif. 1. Synthesis and structure-activity relationship of a class of human immunodeficiency virus type 1 integrase inhibitors.

Abstract: A set of 4-quinolone-3-carboxylic acids bearing different substituents on the condensed benzene ring was designed and synthesized as potential HIV-1 integrase inhibitors structurally related to elvitegravir. Some of the new compounds proved to be able to inhibit the strand transfer step of the virus integration process in the micromolar range. Docking studies and quantum mechanics calculations were used to rationalize these data.

Structure-activity studies on splitomicin derivatives as sirtuin inhibitors and computational prediction of binding mode.

Abstract: NAD (+)-dependent histone deacetylases (sirtuins) are enzymes that cleave acetyl groups from lysines in histones and other proteins. Potent selective sirtuin inhibitors are interesting tools for the investigation of the biological functions of those enzymes and may be future drugs for the treatment of cancer. Splitomicin was among the first two inhibitors that were discovered for yeast sirtuins but showed rather weak inhibition on human enzymes. We present detailed structure-activity relationships on splitomicin derivatives and their inhibition of recombinant Sirt2. To rationalize our experimental results, ligand docking followed by molecular mechanics Poisson-Boltzmann/surface area (MM-PBSA) calculations were carried out. These analyses suggested a molecular basis for the interaction of the beta-phenylsplitomicins with human Sirt2. Protein-based virtual screening resulted in the identification of a novel Sirt2 inhibitor chemotype. Selected inhibitors showed antiproliferative properties and tubulin hyperacetylation in MCF7 breast cancer cells and are promising candidates for further optimization as potential anticancer drugs.

Assessment of programs for ligand binding affinity prediction.

Abstract: The prediction of the binding free energy between a ligand and a protein is an important component in the virtual screening and lead optimization of ligands for drug discovery. To determine the quality of current binding free energy estimation programs, we examined FlexX, X-Score, AutoDock, and BLEEP for their performance in binding free energy prediction in various situations including cocrystallized complex structures, cross docking of ligands to their non-cocrystallized receptors, docking of thermally unfolded receptor decoys to their ligands, and complex structures with "randomized" ligand decoys. In no case was there a satisfactory correlation between the experimental and estimated binding free energies over all the datasets tested. Meanwhile, a strong correlation between ligand molecular weight-binding affinity correlation and experimental predicted binding affinity correlation was found. Sometimes the programs also correctly ranked ligands' binding affinities even though native interactions between the ligands and their receptors were essentially lost because of receptor deformation or ligand randomization, and the programs could not decisively discriminate randomized ligand decoys from their native ligands; this suggested that the tested programs miss important components for the accurate capture of specific ligand binding interactions.

On the Applicability of GPCR Homology Models to Computer-Aided Drug Discovery: A Comparison between In Silico and Crystal Structures of the β2-Adrenergic Receptor

Abstract: The publication of the crystal structure of the β2-adrenergic receptor (β2-AR) proved that G protein-coupled receptors (GPCRs) share a structurally conserved rhodopsin-like 7TM core. Here, to probe to which extent realistic GPCR structures can be recreated through modeling, carazolol was docked at two rhodopsin-based homology models of the human β2-AR. The first featured a rhodopsin-like second extracellular loop, which interfered with ligand docking and with the orientation of several residues in the binding pocket. The second featured a second extracellular loop built completely de novo, which afforded a more accurate model of the binding pocket and a better docking of the ligand. Furthermore, incorporating available biochemical and computational data to the model by correcting the conformation of a single residue lining the binding pocket —Phe290(6.52)—, resulted in significantly improved docking poses. These results support the applicability of GPCR modeling to the design of site-directed mutagenesis ...

Discovery of novel Agonists and antagonists of the free fatty acid receptor 1 (FFAR1) using virtual screening

Abstract: The G-protein-coupled receptor free fatty acid receptor 1 (FFAR1), previously named GPR40, is a possible novel target for the treatment of type 2 diabetes. In an attempt to identify new ligands for this receptor, we performed virtual screening (VS) based on two-dimensional (2D) similarity, three-dimensional (3D) pharmacophore searches, and docking studies by using the structure of known agonists and our model of the ligand binding site, which was validated by mutagenesis. VS of a database of 2.6 million compounds followed by extraction of structural neighbors of functionally confirmed hits resulted in identification of 15 compounds active at FFAR1 either as full agonists, partial agonists, or pure antagonists. Site-directed mutagenesis and docking studies revealed different patterns of ligand-receptor interactions and provided important information on the role of specific amino acids in binding and activation of FFAR1.

Ligand−Protein Docking with Water Molecules

Abstract: 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.

Protein−Ligand Docking against Non-Native Protein Conformers

Abstract: In the validation of protein−ligand docking protocols, performance is mostly measured against native protein conformers, i.e. each ligand is docked into the protein conformation from the structure that contained that ligand. In real-life applications, however, ligands are docked against non-native conformations of the protein, i.e. the apo structure or a structure of a different protein−ligand complex. Here, we have constructed an extensive test set for assessing docking performance against non-native protein conformations. This new test set is built on the Astex Diverse Set (which we recently constructed for assessing native docking performance) and contains 1112 non-native structures for 65 drug targets. Using the protein−ligand docking program GOLD, the Astex Diverse Set and the new Astex Non-native Set, we established that, whereas docking performance (top-ranked solution within 2 A rmsd of the experimental binding mode) is ∼80% for native docking, this drops to 61% for non-native docking. A similar d...

Impact of plasticity and flexibility on docking results for cytochrome P450 2D6: a combined approach of molecular dynamics and ligand docking.

Abstract: Cytochrome P450s (CYPs) exhibit a large plasticity and flexibility in the active site allowing for the binding of a large variety of substrates. The impact of plasticity and flexibility on ligand binding is investigated by docking 65 known CYP2D6 substrates to an ensemble of 2500 protein structures. The ensemble was generated by molecular dynamics simulations of CYP2D6 in complex with five representative substrates. The effect of induced fit, the conformation of Phe483, and thermal motion on the accuracy of site of metabolism (SOM) predictions is analyzed. For future predictions, the three most essential CYP2D6 structures were selected which are suitable for different kinds of ligands. We have developed a binary decision tree to decide which protein structure to dock the ligand into, such that each ligand needs to be docked only once, leading to successful SOM prediction in 80% of the substrates.

Binding of serotonin to the human serotonin transporter. Molecular modeling and experimental validation.

Abstract: Molecular modeling and structure-activity relationship studies were performed to propose a model for binding of the neurotransmitter serotonin (5-HT) to the human serotonin transporter (hSERT). Homology models were constructed using the crystal structure of a bacterial homologue, the leucine transporter from Aquifex aeolicus, as the template and three slightly different sequence alignments. Induced fit docking of 5-HT into hSERT homology models resulted in two different binding modes. Both show a salt bridge between Asp98 and the charged primary amine of 5-HT, and both have the 5-HT C6 position of the indole ring pointing toward Ala173. The difference between the two orientations of 5-HT is an enantiofacial discrimination of the indole ring, resulting in the 5-hydroxyl group of 5-HT being vicinal to either Ser438/Thr439 or Ala169/Ile172/Ala173. To assess the binding experimentally, binding affinities for 5-HT and 17 analogues toward wild type and 13 single point mutants of hSERT were measured using an approach termed paired mutant-ligand analogue complementation (PaMLAC). The proposed ligand-protein interaction was systematically examined by disrupting it through site-directed mutagenesis and re-establishing another interaction via a ligand analogue matching the mutated residue, thereby minimizing the risk of identifying indirect effects. The interactions between Asp98 and the primary amine of 5-HT and the interaction between the C6-position of 5-HT and hSERT position 173 was confirmed using PaMLAC. The measured binding affinities of various mutants and 5-HT analogues allowed for a distinction between the two proposed binding modes of 5-HT and biochemically support the model for 5-HT binding in hSERT where the 5-hydroxyl group is in close proximity to Thr439.

Molecular docking with multi-objective Particle Swarm Optimization

Abstract: The molecular docking problem is to find a good position and orientation for docking a small molecule (ligand) to a larger receptor molecule. In the first part of this paper we propose a new algorithm for solving the docking problem. This algorithm - called ClustMPSO - is based on Particle Swarm Optimization (PSO) and follows a multi-objective approach for comparing the quality of solutions. For the energy evaluation the algorithm uses the binding free energy function that is provided by the Autodock 3.05 tool. The experimental results show that ClustMPSO computes a more diverse set of possible docking conformations than the standard Simulated Annealing and Lamarckian Genetic Algorithm that are incorporated into Autodock. Moreover, ClustMPSO is significantly faster and more reliable in finding good solutions. In the second part of this paper a new approach for the prediction of a docking trajectory is proposed. In this approach the ligand is ''un-docked'' via a controlled random walk that can be biased into a given direction and where only positions are accepted that have an energy level that is below a given threshold.