Latest developments in molecular docking: 2010–2011 in review

The aim of docking is to accurately predict the structure of a ligand within the constraints of a receptor binding site and to correctly estimate the strength of binding. We discuss, in detail, methodological developments that occurred in the docking field in 2010 and 2011, with a particular focus on the more difficult, and sometimes controversial, aspects of this promising computational discipline. The main developments in docking in this period, covered in this review, are receptor flexibility, solvation, fragment docking, postprocessing, docking into homology models, and docking comparisons. Several new, or at least newly invigorated, advances occurred in areas such as nonlinear scoring functions, using machine‐learning approaches. This review is strongly focused on docking advances in the context of drug design, specifically in virtual screening and fragment‐based drug design. Where appropriate, we refer readers to exemplar case studies. Copyright © 2013 John Wiley & Sons, Ltd.     

Receptor–ligand molecular docking

Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein–ligand applications. We summarise the main topics and recent computational and methodological advances in protein–ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.     

Improvements,trends, and new ideas in molecular docking: 2012–2013 in review

Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher‐level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods. Copyright © 2015 John Wiley & Sons, Ltd.     

Curariform antagonists bind in different orientations to acetylcholine-binding protein

Acetylcholine-binding protein (AChBP) recently emerged as a prototype for relating structure to function of the ligand binding domain of nicotinic acetylcholine receptors (AChRs). To understand interactions of competitive antagonists at the atomic structural level, we studied binding of the curare derivatives d-tubocurarine (d-TC) and metocurine to AChBP using computational methods, mutagenesis, and ligand binding measurements. To account for protein flexibility, we used a 2-ns molecular dynamics simulation of AChBP to generate multiple snapshots of the equilibrated dynamic structure to which optimal docking orientations were determined. Our results predict a predominant docking orientation for both d-TC and metocurine, but unexpectedly, the bound orientations differ fundamentally for each ligand. At one subunit interface of AChBP, the side chain of Tyr-89 closely approaches a positively charged nitrogen in d-TC but is farther away from the equivalent nitrogen in metocurine, whereas, at the opposing interface, side chains of Trp-53 and Gln-55 closely approach the metocurine scaffold but not that of d-TC. The different orientations correspond to approximately 170 degrees rotation and approximately 30 degrees degree tilt of the curare scaffold within the binding pocket. Mutagenesis of binding site residues in AChBP, combined with measurements of ligand binding, confirms the different docking orientations. Thus structurally similar ligands can adopt distinct orientations at receptor binding sites, posing challenges for interpreting structure-activity relationships for many drugs.     

Automatic identification and representation of protein binding sites for molecular docking.

Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.     

Molecular docking towards drug discovery

Fueled by advances in molecular structure determination, tools for structure-based drug design are proliferating rapidly. Lead discovery through searching of ligand databases with molecular docking techniques represents an attractive alternative to high-throughput random screening. The size of commercial databases imposes severe computational constraints on molecular docking, compromising the level of calculational detail permitted for each putative ligand. We describe alternative philosophies for docking which effectively address this challenge. With respect to the dynamic aspects of molecular recognition, these strategies lie along a spectrum of models bounded by the Lock-and-Key and Induced-Fit theories for ligand binding. We explore the potential of a rigid model in exploiting species specificity and of a tolerant model in predicting absolute ligand binding affinity. Current molecular docking methods are limited primarily by their ability to rank docked complexes; we therefore place particular emphasis on this aspect of the problem throughout our validation of docking strategies.     

Determination of the binding mode and interacting amino-acids for dibasic H3 receptor antagonists

Due to its involvement in major CNS functions, the histamine H3 receptor (H3R) is the subject of intensive medicinal chemistry investigation, supported by the range of modern drug discovery tools, such as receptor modeling and ligand docking. Although the receptor models described to date share a majority of common traits, they display discrete alternatives in amino-acid conformation, rendering ligand binding modes quite different. Such variations impede structure-based drug design in the H3R field. In the present study, we used a combination of medicinal chemistry, receptor-guided and ligand-based methods to elucidate the binding mode of antagonists. The approaches converged towards a ligand orientation perpendicular to the membrane plane, bridging Glu206 of the transmembrane helix 5 to acidic amino acids of the extracellular loops. This consensus will help future structure-based drug design for H3R ligands.     

Estimating binding affinities by docking/scoring methods using variable protonation states

To investigate the effects of multiple protonation states on protein-ligand recognition, we generated alternative protonation states for selected titratable groups of ligands and receptors. The selection of states was based on the predicted pK(a) of the unbound receptor and ligand and the proximity of titratable groups of the receptor to the binding site. Various ligand tautomer states were also considered. An independent docking calculation was run for each state. Several protocols were examined: using an ensemble of all generated states of ligand and receptor, using only the most probable state of the unbound ligand/receptor, and using only the state giving the most favorable docking score. The accuracies of these approaches were compared, using a set of 176 protein-ligand complexes (15 receptors) for which crystal structures and measured binding affinities are available. The best agreement with experiment was obtained when ligand poses from experimental crystal structures were used. For 9 of 15 receptors, using an ensemble of all generated protonation states of the ligand and receptor gave the best correlation between calculated and measured affinities.     

Site-specific basicities regulate molecular recognition in receptor binding: in silico docking of thyroid hormones

Interactions between thyroid hormone α and β receptors and the eight protonation microspecies of each of the main thyroid hormones (thyroxine, liothyronine, and reverse liothyronine) were investigated and quantitated by molecular modeling. Flexible docking of the various protonation forms of thyroid hormones and high-affinity thyromimetics to the two thyroid receptors was carried out. In this method the role of the ionization state of each basic site could be studied in the composite process of molecular recognition. Our results quantitate at the molecular level how the ionization state and the charge distribution influence the protein binding. The anionic form of the carboxyl group (i.e., carboxylate site) is essential for protein binding, whereas the protonated form of amino group worsens the binding. The protonation state of the phenolate plays a less important role in the receptor affinity; its protonation, however, alters the electron density and the concomitant stacking propensity of the aromatic rings, resulting in a different binding score. The combined results of docking and microspeciation studies show that microspecies with the highest concentration at the pH of blood are not the strongest binding ones. The calculated binding free energy values can be well interpreted in terms of the interactions between the actual sites of the microspecies and the receptor amino acids. Our docking results were validated and compared with biological data from the literature. Since the thyroid hormone receptors influence several physiologic functions, such as metabolic rate, cholesterol and triglyceride levels, and heart frequency, our binding results provide a molecular basis for drug design and development in related therapeutic indications.     

Incorporation of side chain flexibility into protein binding pockets using MTflex

The plasticity of active sites plays a significant role in drug recognition and binding, but the accurate incorporation of ‘receptor flexibility’ remains a significant computational challenge. Many approaches have been put forward to address receptor flexibility in docking studies by generating relevant ensembles on the energy surface. Herein, we describe the Movable Type with flexibility (MT_flex) method that generates ensembles on the more relevant free energy surface in a computationally tractable manner. This novel approach enumerates conformational states based on side chain flexibility and then estimates their relative free energies using the MT methodology. The resultant conformational states can then be used in subsequent docking and scoring exercises. In particular, we demonstrate that using the MT_flex ensembles improves MT’s ability to predict binding free energies over docking only to the crystal structure.     

Homology modelling of CB1 receptor and selection of potential inhibitor against Obesity

Obesity and patient morbidity has become a health concern worldwide. Obesity is associated with over activity of the endocannabinoid system, which is involved in the regulation of appetite, lipogenesis and insulin resistance. Hypothalamic cannabinoid-1 receptor (CB1R) inverse agonists reduce body weight and improve cardiometabolic abnormalities in experimental and human obesity but displayed neuropsychiatric side effects. Hence, there is a need to develop therapeutics which employs blocking peripheral CB1 receptors and still achieve substantial weight loss. In view of the same, adipose tissue CB1 receptors are employed for this study since it is more specific in reducing visceral fat. Computer aided structure based virtual screening finds application to screen novel inhibitors and develop highly selective and potential drug. The rational drug design requires crystal structure for the CB1 receptor. However, the structure for the CB1 receptor is not available in its native form. Thus, we modelled the crystal structure using a lipid G-Protein coupled receptor (PDB: 3V2W, chain A) as template. Furthermore, we have screened a herbal ligand Quercetin [- 2- (3, 4-dihydroxyphenyl) - 3, 5, 7-trihydroxychromen-4-one] a flavonol present in Mimosa pudica based on its better pharmacokinetics and bioavailability profile. This ligand was selected as an ideal lead molecule. The docking of quercetin with CB1 receptor showed a binding energy of -6.56 Kcal/mol with 4 hydrogen bonds, in comparison to the known drug Rimonabant. This data finds application in proposing antagonism of CB1 receptor with Quercetin, for controlling obesity.     

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.     

Molecular modeling studies in the complex between cyclophilin and cyclosporin A.

The structure of the complex between cyclophilin and cyclosporin A is predicted by combining X-ray crystallographic and NMR spectroscopic data using molecular modeling. The drug was placed at the receptor site using a directed docking procedure in which an impulse is imparted to a pre-oriented ligand along an established path. Both ligand and receptor atoms are flexible during the procedure. Two conformers of the MeBMT side chain are shown to result in similar ligand-receptor interaction energies. The models for the drug-receptor complex appear consistent with known experimental data and provide a significant opportunity for the design of compounds with enhanced therapeutic value.     

A molecular docking study of estrogenically active compounds with 1,2-diarylethane and 1,2-diarylethene pharmacophores

Numerous selective estrogen receptor modulators (SERMs) have been synthesized and assayed in recent years. The focus of this study is to apply coarse-grain molecular docking procedures coupled with fine-grain all-atom force field optimization strategies to shed light on the binding mechanisms of currently available estrogen receptor-active compounds. Although the mechanics of ligand binding in estrogen receptors is generally well understood, there is room for surprises. In this paper computational evidence corroborating the experimentally observed type I agonistic binding mode for estradiol (E2) and diethylstilbesterol (DES) and the type II antagonistic binding mode for 4-hydroxytamoxifen and raloxifen is presented. Included in this type I agonistic mode are the DES derivatives, transstilbene and 1,2-diaryldiaminoethane. In addition, a novel ‘type II agonistic’ binding mode for 2,3-diarylimidazolines, 4,5-diarylimidazoles, 2,3-diarylpiperazines is introduced. This mode is stabilized by suggesting alternative hydrogen bond anchor points in the ligand binding domain as potential leads for future drug design.     

Accounting for global protein deformability during protein-protein and protein-ligand docking

Computational docking methods are valuable tools aimed to simplify the costly process of drug development and improvement. Most current approaches assume a rigid receptor structure to allow virtual screening of large numbers of possible ligands and putative binding sites on a receptor molecule. However, inclusion of receptor flexibility can be of critical importance since binding of a ligand can lead to changes in the receptor protein conformation that are sterically necessary to accommodate a ligand. Recent approaches to efficiently account for receptor flexibility during docking simulations are reviewed. In particular, accounting efficiently for global conformational changes of the protein backbone during docking is a still challenging unsolved problem. An approximate method has recently been suggested that is based on relaxing the receptor conformation during docking in pre-calculated soft collective degrees of freedom (M. Zacharias, Rapid protein-ligand docking using soft modes from molecular dynamics simulations to account for protein deformability: binding of FK506 to FKBP, Proteins: Struct., Funct., Genet. 54 (2004) 759-767). Test applications on protein-protein docking and on docking the inhibitor staurosporine to the apo-form of cAMP-dependent protein kinase A catalytic domain indicate significant improvement of docking results compared to rigid docking at a very modest computational demand. Accounting for receptor conformational changes in pre-calculated global degrees of freedom might offer a promising route to improve systematic docking screening simulations.     

The relaxed complex method: Accommodating receptor flexibility for drug design with an improved scoring scheme

An extension of the new computational methodology for drug design, the "relaxed complex" method (J.-H. Lin, A. L. Perryman, J. R. Schames, and J. A. McCammon, Journal of the American Chemical Society, 2002, vol. 24, pp. 5632-5633), which accommodates receptor flexibility, is described. This relaxed complex method recognizes that ligand may bind to conformations that occur only rarely in the dynamics of the receptor. We have shown that the ligand-enzyme binding modes are very sensitive to the enzyme conformations, and our approach is capable of finding the best ligand enzyme complexes. Rapid docking serves as an efficient initial filtering method to screen a myriad of docking modes to a limited set, and it is then followed by more accurate scoring with the MM/PBSA (Molecular Mechanics/Poisson Boltzmann Surface Area) approach to find the best ligand-receptor complexes. The MM/PBSA scorings consistently indicate that the calculated binding modes that are most similar to those observed in the x-ray crystallographic complexes are the ones with the lowest free energies.     

Combining 3D-QSAR,docking, molecular dynamics and MM/PBSA methods to predict binding modes for nonsteroidal selective modulator to glucocorticoid receptor

AL-438 is a selective and dissociated GR (glucocorticoid receptor) agonist. In this letter, the binding mode of AL-438 to GR is predicted by using multiple computational methods including 3D-QSAR, molecular docking and molecular dynamics simulation. This provides a guideline for rational design of novel and dissociated nonsteroidal GR ligand.