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.     

Pex13p: docking or cargo handling protein?

The Src homology 3 (SH3) domain-containing peroxisomal membrane protein Pex13p is an essential component of the import machinery for matrix proteins and forms a binding site for the peroxisomal targeting type I (PTS1) receptor Pex5p. The interaction between these two proteins can be described as novel in several ways. In the yeasts Saccharomyces cerevisiae and Pichia pastoris, the SH3 domain itself is responsible for the interaction but not via the typical P-x-x-P motifs that are common to SH3 ligands as Pex5p lacks such a motif. Instead, a region of Pex5p containing a W-x-x-x-F/Y motif is crucial for this binding. In mammals, again W-x-x-x-F/Y motifs appear to be important for the interaction but the SH3 domain seems not to be the site for Pex5p binding, this being located in the N-terminus of Pex13p. Despite these differences in the details of the Pex13p-Pex5p interaction, the association of the two proteins is a crucial step in Pex5p-mediated protein import into peroxisomes in both yeasts and mammals.     

Protein-protein docking: is the glass half-full or half-empty?

Are current docking methods capable of building complexes from putative component protein structures? Results of recent computational studies, including those of the CAPRI (Critical Assessment of Protein Interactions) competition, were used to determine the key properties for successful docking and introduce a classification of protein complexes based on docking difficulty. Enzyme-inhibitor complexes could be determined with reasonable accuracy - possibly to within a few alternative structures. Results for antigen-antibody pairs are less predictable, and data for small signaling complexes are generally poor. However, moderate amounts of experimental data can remove uncertainty and the methodology is rapidly improving. Transient complexes with large interface areas undergo substantial conformational change and are beyond the reach of current docking methods. The docking of such complexes might therefore require fundamentally new approaches.     

p38γ activation triggers dynamical changes in allosteric docking sites

Mitogen-activated protein kinases (MAPKs) are serine-threonine kinases that participate in signal transduction pathways. p38 MAPKs have four isoforms (p38α, p38β, p38γ, and p38δ) which are involved in multiple cellular functions such as proliferation, differentiation, survival, and migration. MAPK kinases phosphorylate p38s in the dual-phosphorylation motif, Thr-Gly-Tyr, located in their activation loop, which induces a conformational change that increases ATP binding affinity and catalytic activity. Several works have proposed that MAPK dynamics is a key factor in determining their function. However, we still do not understand the dynamical changes that lead to MAPK activation. In this work we have used molecular dynamics techniques to study the dynamical changes associated with p38γ activation, the only fully active MAPK crystallized so far. We performed MD simulations of p38γ in three different states, fully active with ATP, active without ATP, and inactive. We found that the dynamical fluctuations of the docking sites, important for protein-protein interactions, are regulated allosterically by changes in the active site. Interestingly, in the phosphorylated and ATP-bound states the whole protein dynamics lead to concerted motions of whole protein domains in contrast to the inactive state. The binding/unbinding of ATP participates in the reorientation of the two domains and in the regulation of protein plasticity. Our study shows that beyond the conformational changes associated with MAPK activation their correlated dynamics are highly regulated by phosphorylation and ATP binding. This means that MAPK plasticity may have a role in their catalytic activity, specificity, and protein-protein interactions and, therefore, in the outcome of the signaling network.     

An ant colony optimization approach to flexible protein–ligand docking

The prediction of the complex structure of a small ligand with a protein, the so-called protein–ligand docking problem, is a central part of the rational drug design process. For this purpose, we introduce the docking algorithm PLANTS (Protein–Ligand ANT System), which is based on ant colony optimization, one of the most successful swarm intelligence techniques. We study the effectiveness of PLANTS for several parameter settings and present a direct comparison of PLANTS’s performance to a state-of-the-art program called GOLD, which is based on a genetic algorithm and frequently used in the pharmaceutical industry for this task. Last but not least, we also show that PLANTS can make effective use of protein flexibility giving example results on cross-docking and virtual screening experiments for protein kinase A. This article is based on a paper that won the best paper award at ANTS 2006, the 5th International Workshop on Ant Colony Optimization and Swarm Intelligence held in Brussels, Belgium, 2006. This article includes new types of experiments and also the possibility of considering flexibility of protein side-chains.     

Synthesis,molecular docking studies of hybrid benzimidazole as α-glucosidase inhibitor

Thiourea derivatives having benzimidazole 1–17 have been synthesized, characterized by ¹H NMR, ¹³C NMR and EI-MS and evaluated for α-glucosidase inhibition. Identification of potential α-glucosidase inhibitors were done by in vitro screening of 17 thiourea bearing benzimidazole derivatives using Baker’s yeast α-glucosidase enzyme. Compounds 1–17 exhibited a varying degree of α-glucosidase inhibitory activity with IC₅₀ values between 35.83 ± 0.66 and 297.99 ± 1.20 μM which are more better than the standard acarbose (IC₅₀ = 774.5 ± 1.94 μM). Compound 10 and 14 showed significant inhibitory effects with IC₅₀ value 50.57 ± 0.81 and 35.83 ± 0.66 μM, respectively better than the rest of the series. Structure activity relationships were established. Molecular docking studies were performed to understand the binding interaction of the compounds.     

Synthesis,activity and docking studies of phenylpyrimidine–carboxamide Sorafenib derivatives

Two series of Sorafenib derivatives bearing phenylpyrimidine–carboxamide moiety (16a–g and 17a–p) were designed, synthesized and evaluated for the IC₅₀ values against three cancer cell lines (A549, MCF-7 and PC-3). Two selected compounds (17f and 17n) were further evaluated for the activity against VEGFR2/KDR kinase. More than half of the synthesized compounds showed moderate to excellent activity against three cancer cell lines. Compound 17f showed equal activity to Sorafenib against MCF-7 cell line, with the IC₅₀ values of 6.35 ± 0.43 μM. Meanwhile, compound 17n revealed more active than Sorafenib against A549 cell line, with the IC₅₀ values of 3.39 ± 0.37 μM. Structure–activity relationships (SARs) and docking studies indicated that the second series (17a–p) showed more active than the first series (16a–g). What’s more, the introduction of fluoro atom to the phenoxy part played no significant impact on activity. In addition, the presence of electron-donating on aryl group was benefit for the activity.     

CoMFA, HQSAR and molecular docking studies of butitaxel analogues with β-tubulin

Results from biochemical analyses for a series of 20 butitaxel analogues, paclitaxel and docetaxel were used to build two- and three-dimensional quantitative structure-activity relationship (QSAR) models in order to investigate the properties associated with microtubule assembly and stabilization. A comparative molecular field analysis (CoMFA) model was built using steric and electrostatic fields. The CoMFA model yielded an r² of 0.943 and a cross-validated r² (i.e. q²) of 0.376. Hologram quantitative structure-activity relationship (HQSAR) modeling of these same data generated an r² of 0.919 and a q² of 0.471. Contour maps used to visualize the steric and electrostatic contributions associated with activity or lack thereof were, as expected, localized to the varied position of the taxane system. Each analogue was docked successfully into a model of -tubulin derived from previously determined cryoelectron microscopy analyses of the tubulin / heterodimer. All analogues superimposed well with paclitaxel bound to the protein, as well as with each other. Defining the variable region of each structure as the ligand and docking it separately into the paclitaxel site revealed a modest correlation (r²=0.53) between activity and docking energy of all the compounds in the dataset. When only the butitaxel derivatives were considered, the correlation increased to 0.61. The mathematical models derived here provide information for the future development of taxanes.     

Synthesis, β-glucuronidase inhibition and molecular docking studies of hybrid bisindole-thiosemicarbazides analogs

Hybrid bisindole-thiosemicarbazides analogs (1–18) were synthesized and screened for β-glucuronidase activity. All compounds showed varied degree of β-glucuronidase inhibitory potential when compared with standard d-saccharic acid 1,4-lactone (IC₅₀ = 48.4 ± 1.25 μM). Compounds 4, 7, 9, 6, 5, 12, 17 and 18 showed exceptional β-glucuronidase inhibition with IC₅₀ values ranging from 0.1 to 5.7 μM. Compounds 1, 3, 8, 16, 13, 2 and 14 also showed better activities than standard with IC₅₀ values ranging from 7.12 to 15.0 μM. The remaining compounds 10, 11, and 15 showed good inhibitory potential with IC₅₀ values 33.2 ± 0.75, 21.4 ± 0.30 and 28.12 ± 0.25 μM respectively. Molecular docking studies were carried out to confirm the binding interaction of the compounds.     

A protocol for CABS-dock protein–peptide docking driven by side-chain contact information

Background

The characterization of protein–peptide interactions is a challenge for computational molecular docking. Protein–peptide docking tools face at least two major difficulties: (1) efficient sampling of large-scale conformational changes induced by binding and (2) selection of the best models from a large set of predicted structures. In this paper, we merge an efficient sampling technique with external information about side-chain contacts to sample and select the best possible models.

Methods

In this paper we test a new protocol that uses information about side-chain contacts in CABS-dock protein–peptide docking. As shown in our recent studies, CABS-dock enables efficient modeling of large-scale conformational changes without knowledge about the binding site. However, the resulting set of binding sites and poses is in many cases highly diverse and difficult to score.

Results

As we demonstrate here, information about a single side-chain contact can significantly improve the prediction accuracy. Importantly, the imposed constraints for side-chain contacts are quite soft. Therefore, the developed protocol does not require precise contact information and ensures large-scale peptide flexibility in the broad contact area.

Conclusions

The demonstrated protocol provides the extension of the CABS-dock method that can be practically used in the structure prediction of protein–peptide complexes guided by the knowledge of the binding interface.

     

How different from random are docking predictions when ranked by scoring functions?

Docking algorithms predict the structure of protein–protein interactions. They sample the orientation of two unbound proteins to produce various predictions about their interactions, followed by a scoring step to rank the predictions. We present a statistical assessment of scoring functions used to rank near‐native orientations, applying our statistical analysis to a benchmark dataset of decoys of protein–protein complexes and assessing the statistical significance of the outcome in the Critical Assessment of PRedicted Interactions (CAPRI) scoring experiment. A P value was assigned that depended on the number of near‐native structures in the sampling. We studied the effect of filtering out redundant structures and tested the use of pair‐potentials derived using ZDock and ZRank. Our results show that for many targets, it is not possible to determine when a successful reranking performed by scoring functions results merely from random choice. This analysis reveals that changes should be made in the design of the CAPRI scoring experiment. We propose including the statistical assessment in this experiment either at the preprocessing or the evaluation step. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Interaction of prodigiosin with HSA and β-Lg: Spectroscopic and molecular docking studies

Human serum albumin (HSA) and bovine β-lactoglobulin (β-Lg) are both introduced as blood and oral carrier scaffolds with high affinity for a wide range of pharmaceutical compounds. Prodigiosin, a natural three pyrrolic compound produced by Serratia marcescens, exhibits many pharmaceutical properties associated with health benefits. In the present study, the interaction of prodigiosin with HSA and β-Lg was investigated using fluorescence spectroscopy, circular dichroism (CD) and computational docking. Prodigiosin interacts with the Sudlow’s site I of HSA and the calyx of β-Lg with association constant of 4.41 × 10⁴ and 1.99 × 10⁴ M⁻¹ to form 1:1 and 2:3 complexes at 300 K, respectively. The results indicated that binding of prodigiosin to HSA and β-Lg caused strong fluorescence quenching of both proteins through static quenching mechanism. Electrostatic and hydrophobic interactions are the major forces in the stability of PG–HSA complex with enthalpy- and entropy-driving mode, although the formation of prodigiosin–β-Lg complex is entropy-driven hydrophobic associations. CD spectra showed slight conformational changes in both proteins due to the binding of prodigiosin. Moreover, the ligand displacement assay, pH-dependent interaction and protein–ligand docking study confirmed that the prodigiosin binds to residues located in the subdomain IIA and IIIA of HSA and central calyx of β-Lg.     

Discovery of Klotho peptide antagonists against Wnt3 and Wnt3a target proteins using combination of protein engineering,protein–protein docking,peptide docking and molecular dynamics simulations

The Klotho is known as lifespan enhancing protein involved in antagonizing the effect of Wnt proteins. Wnt proteins are stem cell regulators, and uninterrupted exposure of Wnt proteins to the cell can cause stem and progenitor cell senescence, which may lead to aging. Keeping in mind the importance of Klotho in Wnt signaling, in silico approaches have been applied to study the important interactions between Klotho and Wnt3 and Wnt3a (wingless-type mouse mammary tumor virus (MMTV) integration site family members 3 and 3a). The main aim of the study is to identify important residues of the Klotho that help in designing peptides which can act as Wnt antagonists. For this aim, a protein engineering study is performed for Klotho, Wnt3 and Wnt3a. During the theoretical analysis of homology models, unexpected role of number of disulfide bonds and secondary structure elements has been witnessed in case of Wnt3 and Wnt3a proteins. Different in silico experiments were carried out to observe the effect of correct number of disulfide bonds on 3D protein models. For this aim, total of 10 molecular dynamics (MD) simulations were carried out for each system. Based on the protein–protein docking simulations of selected protein models of Klotho with Wnt3 and Wnt3a, different peptides derived from Klotho have been designed. Wnt3 and Wnt3a proteins have three important domains: Index finger, N-terminal domain and a patch of ～10 residues on the solvent exposed surface of palm domain. Protein–peptide docking of designed peptides of Klotho against three important domains of palmitoylated Wnt3 and Wnt3a yields encouraging results and leads better understanding of the Wnt protein inhibition by proposed Klotho peptides. Further in vitro studies can be carried out to verify effects of novel designed peptides as Wnt antagonists.     

RIM determines Ca²+ channel density and vesicle docking at the presynaptic active zone

At presynaptic active zones, neurotransmitter release is initiated by the opening of voltage-gated Ca2+ channels close to docked vesicles. The mechanisms that enrich Ca2+ channels at active zones are, however, largely unknown, possibly because of the limited presynaptic accessibility of most synapses. Here, we have established a Cre-lox based conditional knockout approach at a presynaptically accessible central nervous system synapse, the calyx of Held, to directly study the functions of RIM proteins. Removal of all RIM1/2 isoforms strongly reduced the presynaptic Ca2+ channel density, revealing a role of RIM proteins in Ca2+ channel targeting. Removal of RIMs also reduced the readily releasable pool, paralleled by a similar reduction of the number of docked vesicles, and the Ca2+ channel-vesicle coupling was decreased. Thus, RIM proteins co-ordinately regulate key functions for fast transmitter release, enabling a high presynaptic Ca2+ channel density and vesicle docking at the active zone.     

Molecular mechanism of δ-dendrotoxin-potassium channel recognition explored by docking and molecular dynamic simulations

δ-Dendrotoxin, isolated from mamba snake venom, has 57 residues cross-linked by three disulfide bridges. The protein shares a pharmacological activity with other animal toxins, the potent blockade of potassium channels, but is structurally unrelated to toxins of different species. We employed alanine-scanning mutagenesis to explore the molecular mechanism of δ-dendrotoxin binding to potassium channels, using protein-protein docking and molecular dynamic simulations. In our reasonable model of the δ-dendrotoxin-ShaKv1.1 complex, δ-dendrotoxin interacted mainly with the N-terminal region and the turn of two antiparallel β-sheets of the channel. This binding mode could well explain the functional roles of critical residues in δ-dendrotoxin and the ShaKv1.1 channel. Structural analysis indicated that the critical Lys6 residue of δ-dendrotoxin plugged its side chain into a channel selectivity filter. Another two critical δ-dendrotoxin residues, Lys3 and Arg10, were found to contact channel residues through strong polar and nonpolar interactions, especially salt-bridge interactions. As for the ShaKv1.1 channel, the channel turrets were found in the "half-open state," and two of four Glu423 in the turrets of the channel B and D chains could interact, respectively, with Lys3 and Lys26 of δ-dendrotoxin through electrostatic interactions. The essential Asp431 channel residue was found to associate electrostatically with Arg10 of δ-dendrotoxin, and a critical Tyr449 channel residue was just under the channel-interacting surface of δ-dendrotoxin. Together, these novel data may accelerate the structure-function research of toxins in the dendrotoxin family and be of significant value in revealing the diverse interactions between animal toxins and potassium channels.     

Molecular docking studies and synthesis of novel bisbenzimidazole derivatives as inhibitors of α-glucosidase

A series of bisbenzimidazole derivatives starting from o-phenylenediamine and 4-nitro-o-phenylenediamine were prepared with oxalic acid. Most of the reactions were conducted using both the microwave and conventional methods to compare yields and reaction times. The operational simplicity, environmental friendly conditions and high yield in a significantly short reaction time were the major benefits. All substances’ inhibitory activities against α-glucosidase were evaluated. The results may suggest a significant role for the nature of bisbenzimidazole compounds in their inhibitory action against α-glucosidase. They showed different range of α-glucosidase inhibitory potential with IC₅₀ value ranging between 0.44 ± 0.04 and 6.69 ± 0.01 μM when compared to the standard acarbose (IC₅₀, 13.34 ± 1.26 μM). This has described a new class of α-glucosidase inhibitors. Molecular docking studies were done for all compounds to identify important binding modes responsible for inhibition activity of α-glucosidase.