Solvated protein–protein docking using Kyte‐Doolittle‐based water preferences

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on water‐mediated contact probabilities. The latter were derived from an analysis of water contact frequencies from high‐resolution crystal structures. Here, we introduce a simple water‐mediated amino acid–amino acid contact probability scale derived from the Kyte‐Doolittle hydrophobicity scale and assess its performance on the largest high‐resolution dataset developed to date for solvated docking. Both scales yield high‐quality docking results. The novel and simple hydrophobicity scale, which should reflect better the physicochemical principles underlying contact propensities, leads to a performance improvement of around 10% in ranking, cluster quality and water recovery at the interface compared with the statistics‐based original solvated docking protocol. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Using situs for flexible and rigid-body fitting of multiresolution single-molecule data

We describe here a set of multiresolution visualization and docking procedures that we refer to as the Situs package. The package was developed to provide an efficient and robust method for the fitting of atomic structures into low-resolution data. The current release was optimized specifically for the visualization and docking of single molecules. A novel 3D graphics viewer, volslice3d, was developed for the package to provide an immersive virtual reality environment for measuring and rendering volumetric data sets. The precision of single-molecule, rigid-body docking was tested on simulated (noise-free) low-resolution density maps. For spatial resolutions near 20 A typically arising in electron microscopy image reconstructions, a docking precision on the order of 1 A can be achieved. The shape-matching score captured the correct solutions in all 10 trial cases and was sufficiently stringent to yield unique matches in 8 systems. Novel routines were developed for the flexible docking of atomic structures whose shape deviates from the corresponding low-resolution shape. Test calculations on isoforms of actin and lactoferrin demonstrate that the flexible docking faithfully reproduces conformational differences with a precision < 2 A if atomic structures are locally conserved.     

Flexible docking using tabu search and an empirical estimate of binding affinity

This article describes the implementation of a new docking approach. The method uses a Tabu search methodology to dock flexibly ligand molecules into rigid receptor structures. It uses an empirical objective function with a small number of physically based terms derived from fitting experimental binding affinities for crystallographic complexes. This means that docking energies produced by the searching algorithm provide direct estimates of the binding affinities of the ligands. The method has been tested on 50 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. All water molecules are removed from the structures and ligand molecules are minimized in vacuo before docking. The lowest energy geometry produced by the docking protocol is within 1.5 Å root-mean square of the experimental binding mode for 86% of the complexes. The lowest energies produced by the docking are in fair agreement with the known free energies of binding for the ligands. Proteins 33:367–382, 1998. © 1998 Wiley-Liss, Inc.     

Receptor-guided 3D-QSAR approach for the discovery of c-kit tyrosine kinase inhibitors

Studies of the the three-dimensional quantitative structure-activity relationships for ninety-five c-kit tyrosine kinase inhibitors were performed. Based on a co-crystallized compound (1 T46), known inhibitors were aligned with c-kit by induced-fit docking, and multiple training/test set splitting was performed to validate the selected pharmacophore model. The best pharmacophore model consisted of five features: one hydrogen-bond donor and four aromatic rings. Reliable statistics were obtained (R(2) = 0.95, R(pred) (2) = 0.75), and the model was validated by using it to select c-kit inhibitors from a database; 82.1% of the hits it retrieved were active. Accordingly, our model can be reliably used to identify new c-kit inhibitors, and can provide useful information when designing new inhibitors.     

Quantitative analysis of ERK2 interactions with substrate proteins: roles for kinase docking domains and activity in determining binding affinity

Extracellular signal-regulated kinase-1 and -2 (ERK1/2) proteins regulate a variety of cellular functions, including cell proliferation and differentiation, by interacting with and phosphorylating substrate proteins. Two docking sites, common docking (CD/ED) domain and F-site recruitment site (FRS), on ERK proteins have been identified. Specific interactions with the CD/ED domain and the FRS occur with substrates containing a docking site for ERK and JNK, LXL (DEJL) motif (D-domain) and a docking site for ERK, FXF (DEF) motif (F-site), respectively. However, the relative contributions of the ERK docking sites in mediating substrate interactions that allow efficient phosphate transfer are largely unknown. In these studies, we provide a quantitative analysis of ERK2 interactions with substrates using surface plasmon resonance to measure real time protein-protein interactions. ERK2 interacted with ELK-1 (DEF and DEJL motifs), RSK-1 (DEJL motif), and c-Fos (DEF motif) with K(D) values of 0.25, 0.15, and 0.97 μM, respectively. CD/ED domain mutations inhibited interactions with ELK-1 and RSK-1 by 6-fold but had no effect on interactions with c-Fos. Select mutations in FRS residues differentially inhibited ELK-1 or c-Fos interactions with ERK2 but had little effect on RSK-1 interactions. Mutations in both the ED and FRS docking sites completely inhibited ELK-1 interactions but had no effect on interactions with stathmin, an ERK substrate whose docking site is unknown. The phosphorylation status of ERK2 did not affect interactions with RSK-1 or c-Fos but did inhibit interactions with ELK-1 and stathmin. These studies provide a quantitative evaluation of specific docking domains involved in mediating interactions between ERK2 and protein substrates and define the contributions of these interactions to phosphate transfer.     

Open syntaxin docks synaptic vesicles

Synaptic vesicles dock to the plasma membrane at synapses to facilitate rapid exocytosis. Docking was originally proposed to require the soluble N-ethylmaleimide–sensitive fusion attachment protein receptor (SNARE) proteins; however, perturbation studies suggested that docking was independent of the SNARE proteins. We now find that the SNARE protein syntaxin is required for docking of all vesicles at synapses in the nematode Caenorhabditis elegans. The active zone protein UNC-13, which interacts with syntaxin, is also required for docking in the active zone. The docking defects in unc-13 mutants can be fully rescued by overexpressing a constitutively open form of syntaxin, but not by wild-type syntaxin. These experiments support a model for docking in which UNC-13 converts syntaxin from the closed to the open state, and open syntaxin acts directly in docking vesicles to the plasma membrane. These data provide a molecular basis for synaptic vesicle docking.     

A simple reference state makes a significant improvement in near-native selections from structurally refined docking decoys

Near-native selections from docking decoys have proved challenging especially when unbound proteins are used in the molecular docking. One reason is that significant atomic clashes in docking decoys lead to poor predictions of binding affinities of near native decoys. Atomic clashes can be removed by structural refinement through energy minimization. Such an energy minimization, however, will lead to an unrealistic bias toward docked structures with large interfaces. Here, we extend an empirical energy function developed for protein design to protein-protein docking selection by introducing a simple reference state that removes the unrealistic dependence of binding affinity of docking decoys on the buried solvent accessible surface area of interface. The energy function called EMPIRE (EMpirical Protein-InteRaction Energy), when coupled with a refinement strategy, is found to provide a significantly improved success rate in near native selections when applied to RosettaDock and refined ZDOCK docking decoys. Our work underlines the importance of removing nonspecific interactions from specific ones in near native selections from docking decoys.     

Docking and DFT studies on ligand binding to Quercetin 2,3-dioxygenase

Simple molecular docking calculations on quercetin, kojic acid and diethylcarbamatodithoic acid using the software package MOE are shown to be close to the geometries reported in the X-ray crystal structures of the protein co-crystallized with the respective ligands. Furthermore, DFT optimization of the docked conformations is shown to reproduce the essential features of previous studies on quercetin, showing that docking can be used to provide good starting structures for mechanistic study. The flavone ligand, lacking the hydroxyl group of the quercetin is shown by docking to be unable to approach closely the copper atom, indicating the necessity of the presence of the hydroxyl group and providing a prediction of the likely binding environment of this ligand.     

Docking of a single phage lambda to its membrane receptor maltoporin as a time-resolved event

We have been able to observe the first step in bacteriophage infection, the docking of phage lambda to its membrane receptor maltoporin, at the single-particle level. High-resolution conductance recording from a single trimeric maltoporin channel reconstituted into a planar lipid bilayer has allowed detection of the simultaneous and irreversible interaction of the phage tail with all three monomers of the receptor. The formation of a phage-maltoporin complex affects the channel transport properties. Our analysis demonstrates that phage attaches symmetrically to all three receptor monomers. The statistics of sugar binding to the phage-receptor complex on the side opposite to phage docking show that the monomers of maltoporin still bind sugar independently, with the kinetic constants expected from those of the phage-free receptor. This finding suggests that phage docking does not distort the structure of the receptor, and that the phage-binding regions are close to, but do not overlap with, the sugar-binding domains of the maltoporin monomers. However, ion fluxes through the pores of maltoporin in the phage-receptor complex share a new common pathway. We expect that the present study contributes to the current needs for structural information on the functional complexes involved in intercellular recognition.     

Proposed docking interface between peptidoglycan and the target recognition domain of zoocin A

A docking model is proposed for the target recognition domain of the lytic exoenzyme zoocin A with the peptidoglycan on the outer cell surface of sensitive bacterial strains. Solubilized fragments from such peptidoglycans perturb specific backbone and side chain amide resonances in the recombinant form of the domain designated rTRD as detected in two-dimensional ¹H–¹⁵N correlation NMR spectra. The affected residues comprise a shallow surface cleft on the protein surface near W115, N53, N117, and Q105 among others, which interacts with the peptide portion of the peptidoglycan. Calculations with AutoDock Vina provide models of the docking interface. There is approximate homology between the rTDR-peptidoglycan docking site and the antigen binding site of Fab antibodies with the immunoglobin fold. EDTA was also found to bind to rTRD, but at a site distinct from the proposed peptidoglycan docking site.     

Prediction of protein-protein interactions: the CAPRI experiment, its evaluation and implications

Given the increasing interest in protein-protein interactions, the prediction of these interactions from sequence and structural information has become a booming activity. CAPRI, the community-wide experiment for assessing blind predictions of protein-protein interactions, is playing an important role in fostering progress in docking procedures. At the same time, novel methods are being derived for predicting regions of a protein that are likely to interact and for characterizing putative intermolecular contacts from sequence and structural data. Together with docking procedures, these methods provide an integrated computational approach that should be a valuable complement to genome-scale experimental studies of protein-protein interactions.     

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

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

Protein-RNA Complexes and Efficient Automatic Docking: Expanding RosettaDock Possibilities

Protein-RNA complexes provide a wide range of essential functions in the cell. Their atomic experimental structure solving, despite essential to the understanding of these functions, is often difficult and expensive. Docking approaches that have been developed for proteins are often challenging to adapt for RNA because of its inherent flexibility and the structural data available being relatively scarce. In this study we adapted the RosettaDock protocol for protein-RNA complexes both at the nucleotide and atomic levels. Using a genetic algorithm-based strategy, and a non-redundant protein-RNA dataset, we derived a RosettaDock scoring scheme able not only to discriminate but also score efficiently docking decoys. The approach proved to be both efficient and robust for generating and identifying suitable structures when applied to two protein-RNA docking benchmarks in both bound and unbound settings. It also compares well to existing strategies. This is the first approach that currently offers a multi-level optimized scoring approach integrated in a full docking suite, leading the way to adaptive fully flexible strategies.     

Identification of near-native structures by clustering protein docking conformations

Most state-of-the-art protein-protein docking algorithms use the Fast Fourier Transform (FFT) technique to sample the six-dimensional translational and rotational space. Scoring functions including shape complementarity, electrostatics, and desolvation are usually exploited in ranking the docking conformations. While these rigid-body docking methods provide good performance in bound docking, using unbound structures as input frequently leads to a high number of false positive hits. For the purpose of better selecting correct docking conformations, we structurally cluster the docking decoys generated by four widely-used FFT-based protein-protein docking methods. In all cases, the selection based on cluster size outperforms the ranking based on the inherent scoring function. If we cluster decoys from different servers together, only marginal improvement is obtained in comparison with clustering decoys from the best individual server. A collection of multiple decoy sets of comparable quality will be the key to improve the clustering result from meta-docking servers.     

Structure-based virtual screening against SARS-3CL(pro) to identify novel non-peptidic hits

Severe acute respiratory syndrome is a highly infectious upper respiratory tract disease caused by SARS-CoV, a previously unidentified human coronavirus. SARS-3CL(pro) is a viral cysteine protease critical to the pathogen's life cycle and hence a therapeutic target of importance. The recently elucidated crystal structures of this enzyme provide an opportunity for the discovery of inhibitors through rational drug design. In the current study, Gold docking program was utilized to conduct extensive docking studies against the target crystal structure to develop a robust and predictive docking protocol. The validated docking protocol was used to conduct a structure-based virtual screening of the Asinex Platinum collection. Biological evaluation of a screened selection of compounds was carried out to identify novel inhibitors of the viral protease.     

Exploration of the transition state for tertiary structure formation between an RNA helix and a large structured RNA

Docking of the P1 duplex into the pre-folded core of the Tetrahymena group I ribozyme exemplifies the formation of tertiary interactions in the context of a complex, structured RNA. We have applied Phi-analysis to P1 docking, which compares the effects of modifications on the rate constant for docking (k(dock)) with the effects on the docking equilibrium (K(dock)). To accomplish this we used a single molecule fluorescence resonance energy transfer assay that allows direct determination of the rate constants for formation of thermodynamically favorable, as well as unfavorable, states. Modification of the eight groups of the P1 duplex that make tertiary interactions with the core and changes in solution conditions decrease K(dock) up to 500-fold, whereas k(dock) changes by 相似文献   

Pharmacophore models generation by catalyst and phase consensus-based virtual screening protocol against PI3Kα inhibitors

Phosphoinositide 3-kinases (PI3Ks) family has emerged as promising targets for novel therapeutic agents against neoplastic diseases. Pharmacophore and 3D-quantitative structure–activity relationship modelling were applied to study the structure–activity relationship of PI3K inhibitors. The best HypoGen pharmacophore hypothesis Hypo1 with a correlation coefficient of 0.961 consists of one hydrogen-bond acceptor, one hydrogen-bond donor and two hydrophobic features, whereas the best phase hypothesis AADRRR.378 with favourable statistics (q² = 0.7368, r² = 0.9863) has two hydrogen-bond acceptors, one hydrogen-bond donor and three ring aromatic features. Multiple methods, such as Fischer validation, molecular docking and mapping of test set molecules, were carried out to validate these pharmacophore models. Furthermore, a comparative molecular similarity indices analysis candidate hypothesis model was generated as a supplement of pharmacophore hypothesis. Detailed protein–ligand binding information obtained by Glide was utilised in compound optimisation and virtual screening. A molecular database of 133 known inhibitors and 6179 decoys was built for a screening test to quantitatively analyse various hypotheses and scoring parameters. Finally, we designed a workflow integrating HypoGen pharmacophore searching, phase pharmacophore searching and molecular docking for screening the database. With an improved criterion of enrichment factor (EF = 17.43) and ROC curve (AUC = 0.946), this workflow would provide us an original method for novel PI3K inhibitors.     

Modelling the binding mode of macrocycles: Docking and conformational sampling

Drug discovery is increasingly tackling challenging protein binding sites regarding molecular recognition and druggability, including shallow and solvent-exposed protein-protein interaction interfaces. Macrocycles are emerging as promising chemotypes to modulate such sites. Despite their chemical complexity, macrocycles comprise important drugs and offer advantages compared to non-cyclic analogs, hence the recent impetus in the medicinal chemistry of macrocycles. Elaboration of macrocycles, or constituent fragments, can strongly benefit from knowledge of their binding mode to a target. When such information from X-ray crystallography is elusive, computational docking can provide working models. However, few studies have explored docking protocols for macrocycles, since conventional docking methods struggle with the conformational complexity of macrocycles, and also potentially with the shallower topology of their binding sites. Indeed, macrocycle binding mode prediction with the mainstream docking software GOLD has hardly been explored. Here, we present an in-depth study of macrocycle docking with GOLD and the ChemPLP scores. First, we summarize the thorough curation of a test set of 41 protein-macrocycle X-ray structures, raising the issue of lattice contacts with such systems. Rigid docking of the known bioactive conformers was successful (three top ranked poses) for 92.7% of the systems, in absence of crystallographic waters. Thus, without conformational search issues, scoring performed well. However, docking success dropped to 29.3% with the GOLD built-in conformational search. Yet, the success rate doubled to 58.5% when GOLD was supplied with extensive conformer ensembles docked rigidly. The reasons for failure, sampling or scoring, were analyzed, exemplified with particular cases. Overall, binding mode prediction of macrocycles remains challenging, but can be much improved with tailored protocols. The analysis of the interplay between conformational sampling and docking will be relevant to the prospective modelling of macrocycles in general.     

Combining substrate dynamics, binding statistics, and energy barriers to rationalize regioselective hydroxylation of octane and lauric acid by CYP102A1 and mutants

Hydroxylations of octane and lauric acid by Cytochrome P450-BM3 (CYP102A1) wild-type and three active site mutants--F87A, L188Q/A74G, and F87V/L188Q/A74G--were rationalized using a combination of substrate orientation from docking, substrate binding statistics from molecular dynamics simulations, and barrier energies for hydrogen atom abstraction from quantum mechanical calculations. Wild-type BM3 typically hydroxylates medium- to long-chain fatty acids on subterminal (omega-1, omega-2, omega-3) but not the terminal (omega) positions. The known carboxylic anchoring site Y51/R47 for lauric acid, and hydrophobic interactions and steric exclusion, mainly by F87, for octane as well as lauric acid, play a role in the binding modes of the substrates. Electrostatic interactions between the protein and the substrate strongly modulate the substrate's regiodependent activation barriers. A combination of the binding statistics and the activation barriers of hydrogen-atom abstraction in the substrates is proposed to determine the product formation. Trends observed in experimental product formation for octane and lauric acid by wild-type BM3 and the three active site mutants were qualitatively explained. It is concluded that the combination of substrate binding statistics and hydrogen-atom abstraction barrier energies is a valuable tool to rationalize substrate binding and product formation and constitutes an important step toward prediction of product ratios.