Computational modeling of human coreceptor CCR5 antagonist as a HIV-1 entry inhibitor: using an integrated homology modeling, docking, and membrane molecular dynamics simulation analysis approach

Computational study of the structural ensemble of CC chemokine receptor type 5 (CCR5) and its interactions with different ligands

CC Chemokine receptor 5 (CCR5), a member of the Superfamily of G Protein-Coupled Receptors (GPCRs), is an important effector in multiple physiopathological processes such as inflammatory and infectious entities, including central nervous system neuroinflammatory diseases such as Alzheimer's disease, recovery from nervous injuries, and in the HIV-AIDS infective processes. Thus, CCR5 is an attractive target for pharmacological modulation. Since maraviroc was described as a CCR5 ligand that modifies the HIV-AIDS progression, multiple efforts have been developed to describe the functionality of the receptor. In this work, we characterized key structural features of the CCR5 receptor employing extensive atomistic molecular dynamics (MD) in its apo form and in complex with an endogenous agonist, the chemokine CCL5/RANTES, an HIV entry inhibitor, the partial inverse agonist maraviroc, and the experimental antagonists Compound 21 and 34, aiming to elucidate the structural features and mechanistic processes that constitute its functional states, contributing with structural details and a general understanding of this relevant system.

Allosteric mechanism of an oximino-piperidino-piperidine antagonist for the CCR5 chemokine receptor

The first step for the HIV-1 virus infecting host cell is bound with the CCR5 chemokine receptor. A set of allosteric inhibitors of oximino-piperidino-piperidine antagonists for CCR5 chemokine receptor was discovered. However, the allosteric mechanism of these inhibitors is still unsolved. Therefore, residue-level dynamics correlation network combining with on molecular dynamics simulation was used to investigate the allosteric mechanism. The dynamics correlation network of bound CCR5 is significantly different from that of free CCR5. The community of the most active complex suggests that the allosteric information can freely transfer from the allosteric site to the effector site of the second extracellular loop, while the information transfers bottleneck for the less active one. Here, a hypothesis was proposed that "binding-induced allosteric mechanism" was used to reveal the allosteric regulation of antagonists and the network perturbation confirmed it. Finally, the shortest path algorithm was used to identify the possible allosteric pathway with Gly173-Lys171-Thr177-Tyr89-LIG which was evaluated by the network perturbation of key residue. Furthermore, the efficiency of allostery for the most active system is the highest among these antagonist complexes. The strategy targeting the allosteric pathway can be used to design novel inhibitors of HIV-1 virus.

Investigation of Inhibition Mechanism of Chemokine Receptor CCR5 by Micro-second Molecular Dynamics Simulations

Chemokine receptor 5 (CCR5) belongs to G protein coupled receptors (GPCRs) and plays an important role in treatment of human immunodeficiency virus (HIV) infection since HIV uses CCR5 protein as a co-receptor. Recently, the crystal structure of CCR5-bound complex with an approved anti-retroviral drug (maroviroc) was resolved. During the crystallization procedure, amino acid residues (i.e., Cys224, Arg225, Asn226 and Glu227) at the third intra-cellular loop were replaced by the rubredoxin for stability reasons. In the current study, we aimed to understand the impact of the incorporated rubredoxin on the conformations of TM domains of the target protein. For this reason, rubredoxin was deleted from the crystal structure and the missing amino acids were engineered. The resultant structure was subjected to long (μs) molecular dynamics (MD) simulations to shed light into the inhibitory mechanism. The derived model structure displayed a significant deviation in the cytoplasmic domain of TM5 and IC3 in the absence of rubredoxin. The principal component analyses (PCA) and MD trajectory analyses revealed important structural and dynamical differences at apo and holo forms of the CCR5.

In silico characterization of binding mode of CCR8 inhibitor: homology modeling, docking and membrane based MD simulation study

Human CC-chemokine receptor 8 (CCR8) is a crucial drug target in asthma that belongs to G-protein-coupled receptor superfamily, which is characterized by seven transmembrane helices. To date, there is no X-ray crystal structure available for CCR8; this hampers active research on the target. Molecular basis of interaction mechanism of antagonist with CCR8 remains unclear. In order to provide binding site information and stable binding mode, we performed modeling, docking and molecular dynamics (MD) simulation of CCR8. Docking study of biaryl-ether-piperidine derivative (13C) was performed inside predefined CCR8 binding site to get the representative conformation of 13C. Further, MD simulations of receptor and complex (13C-CCR8) inside dipalmitoylphosphatidylcholine lipid bilayers were performed to explore the effect of lipids. Results analyses showed that the Gln91, Tyr94, Cys106, Val109, Tyr113, Cys183, Tyr184, Ser185, Lys195, Thr198, Asn199, Met202, Phe254, and Glu286 were conserved in both docking and MD simulations. This indicated possible role of these residues in CCR8 antagonism. However, experimental mutational studies on these identified residues could be effective to confirm their importance in CCR8 antagonism. Furthermore, calculated Coulombic interactions represented the crucial roles of Glu286, Lys195, and Tyr113 in CCR8 antagonism. Important residues identified in this study overlap with the previous non-peptide agonist (LMD-009) binding site. Though, the non-peptide agonist and currently studied inhibitor (13C) share common substructure, but they differ in their effects on CCR8. So, to get more insight into their agonist and antagonist effects, further side-by-side experimental studies on both agonist (LMD-009) and antagonist (13C) are suggested.

Insights into the binding modes of CC chemokine receptor 4 (CCR4) inhibitors: a combined approach involving homology modelling, docking, and molecular dynamics simulation studies

CC chemokine receptor 4 (CCR4), a G protein-coupled receptor (GPCR), plays a vital role in the progression of asthma, T-cell lymphoma, inflammation, and Alzheimer's disease. To date, the structure of CCR4 has not been determined. Therefore, the nature of the interactions between inhibitors and CCR4 is not well known. In this study, we used CCR5 as a template to model the structure of CCR4. Docking studies were performed for four naphthalene-sulphonamide derivatives and crucial ligand-protein interactions were analysed. Molecular dynamics (MD) simulations of these complexes (100 ns each) were carried out to gain insights into the interactions between ligands and CCR4. MD simulations revealed that the residues identified by the docking were displaced and new residues were inserted near the ligands. Results of a principal component analysis (PCA) suggested that CCR4 unfolds at the extracellular site surrounding the ligands. Our simulations identified crucial residues involved in CCR4 antagonism, which were supported by previous mutational studies. Additionally, we identified Ser3.29, Leu3.33, Ser5.39, Phe6.47, Ile7.35, Thr7.38, Thr7.40, and Ala7.42 as residues that play crucial roles in CCR4 antagonism. Mutational studies will help elucidate the significance of these residues in CCR4 antagonism. An understanding of ligand-CCR4 interactions might aid in the design of novel CCR4 inhibitors.

Anti-HIV drug development through computational methods

Although highly active antiretroviral therapy (HAART) is effective in controlling the progression of AIDS, the emergence of drug-resistant strains increases the difficulty of successful treatment of patients with HIV infection. Increasing numbers of patients are facing the dilemma that comes with the running out of drug combinations for HAART. Computational methods play a key role in anti-HIV drug development. A substantial number of studies have been performed in anti-HIV drug development using various computational methods, such as virtual screening, QSAR, molecular docking, and homology modeling, etc. In this review, we summarize recent advances in the application of computational methods to anti-HIV drug development for five key targets as follows: reverse transcriptase, protease, integrase, CCR5, and CXCR4. We hope that this review will stimulate researchers from multiple disciplines to consider computational methods in the anti-HIV drug development process.

Integrated computational tools for identification of CCR5 antagonists as potential HIV-1 entry inhibitors: homology modeling, virtual screening, molecular dynamics simulations and 3D QSAR analysis

Using integrated in-silico computational techniques, including homology modeling, structure-based and pharmacophore-based virtual screening, molecular dynamic simulations, per-residue energy decomposition analysis and atom-based 3D-QSAR analysis, we proposed ten novel compounds as potential CCR5-dependent HIV-1 entry inhibitors. Via validated docking calculations, binding free energies revealed that novel leads demonstrated better binding affinities with CCR5 compared to maraviroc, an FDA-approved HIV-1 entry inhibitor and in clinical use. Per-residue interaction energy decomposition analysis on the averaged MD structure showed that hydrophobic active residues Trp86, Tyr89 and Tyr108 contributed the most to inhibitor binding. The validated 3D-QSAR model showed a high cross-validated r_cv² value of 0.84 using three principal components and non-cross-validated r² value of 0.941. It was also revealed that almost all compounds in the test set and training set yielded a good predicted value. Information gained from this study could shed light on the activity of a new series of lead compounds as potential HIV entry inhibitors and serve as a powerful tool in the drug design and development machinery.