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Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents.

ABSTRACT: A novel virtual screening approach is implemented herein, which is a further improvement of our previously published "target-bound pharmacophore modeling approach". The generated pharmacophore library is based only on highly contributing amino acid residues, instead of arbitrary pharmacophores, which are most commonly used in the conventional approaches in literature. Highly contributing amino acid residues were distinguished based on free binding energy contributions obtained from calculation from molecular dynamic (MD) simulations. To the best of our knowledge; this is the first attempt in the literature using such an approach; previous approaches have relied on the docking score to generate energy-based pharmacophore models. However, docking scores are reportedly unreliable. Thus, we present a model for a per-residue energy decomposition, constructed from MD simulation ensembles generating a more trustworthy pharmacophore model, which can be applied in drug discovery workflow. This work is aimed at introducing a more rational approach to the field of drug design, rather than comparing the validity of this approach against those previously reported. We recommend additional computational and experimental work to further validate this approach. This approach was used to screen for potential reverse transcriptase inhibitors using the pharmacophoric features of compound GSK952. The complex was subjected to docking, thereafter, MD simulation confirmed the stability of the system. Experimentally determined inhibitors with known HIV-reverse transcriptase inhibitory activity were used to validate the protocol. Two potential hits (ZINC46849657 and ZINC54359621) showed a significant potential with regard to free binding energy. Reported results obtained from this work confirm that this new approach is favorable in the future of the drug design industry.

SUBMITTER: Cele FN

PROVIDER: S-EPMC4833373 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents.

Cele Favourite N FN Ramesh Muthusamy M Soliman Mahmoud Es ME

Drug design, development and therapy 20160411

A novel virtual screening approach is implemented herein, which is a further improvement of our previously published "target-bound pharmacophore modeling approach". The generated pharmacophore library is based only on highly contributing amino acid residues, instead of arbitrary pharmacophores, which are most commonly used in the conventional approaches in literature. Highly contributing amino acid residues were distinguished based on free binding energy contributions obtained from calculation f ...[more]

PMID: 27114700

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Project description:Background and objectiveThe current coronavirus disease-2019 (COVID-19) pandemic has triggered a worldwide health and economic crisis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes the disease and completes its life cycle using the RNA-dependent RNA-polymerase (RdRp) enzyme, a prominent target for antivirals. In this study, we have computationally screened ∼690 million compounds from the ZINC20 database and 11,698 small molecule inhibitors from DrugBank to find existing and novel non-nucleoside inhibitors for SARS-CoV-2 RdRp.MethodsHerein, a combination of the structure-based pharmacophore modeling and hybrid virtual screening methods, including per-residue energy decomposition-based pharmacophore screening, molecular docking, pharmacokinetics, and toxicity evaluation were employed to retrieve novel as well as existing RdRp non-nucleoside inhibitors from large chemical databases. Besides, molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method were used to investigate the binding stability and calculate the binding free energy of RdRp-inhibitor complexes.ResultsBased on docking scores and significant binding interactions with crucial residues (Lys553, Arg557, Lys623, Cys815, and Ser816) in the RNA binding site of RdRp, three existing drugs, ZINC285540154, ZINC98208626, ZINC28467879, and five compounds from ZINC20 (ZINC739681614, ZINC1166211307, ZINC611516532, ZINC1602963057, and ZINC1398350200) were selected, and the conformational stability of RdRp due to their binding was confirmed through molecular dynamics simulation. The free energy calculations revealed these compounds possess strong binding affinities for RdRp. In addition, these novel inhibitors exhibited drug-like features, good absorption, distribution, metabolism, and excretion profile and were found to be non-toxic.ConclusionThe compounds identified in the study by multifold computational strategy can be validated in vitro as potential non-nucleoside inhibitors of SARS-CoV-2 RdRp and holds promise for the discovery of novel drugs against COVID-19 in future.

Project description:N348I in HIV-1 reverse transcriptase (RT) confers resistance to zidovudine (AZT) and nevirapine. Biochemical studies demonstrated that N348I indirectly increases AZT resistance by decreasing the frequency of secondary ribonuclease H (RNase H) cleavages that reduce the RNA/DNA duplex length of the template/primer (T/P) and diminish the efficiency of AZT-monophosphate (MP) excision. By contrast, there is some discrepancy in the literature in regard to the mechanisms associated with nevirapine resistance: one study suggested that it is due to decreased inhibitor binding while others suggest that it may be related to the decreased RNase H cleavage phenotype. From a structural perspective, N348 in both subunits of RT resides distal to the enzyme's active sites, to the T/P binding tract and to the nevirapine-binding pocket. As such, the structural mechanisms associated with the resistance phenotypes are not known.Using a novel modelled structure of RT in complex with an RNA/DNA T/P, we identified a putative interaction between the ?14-?15 loop in the p51 subunit of RT and the RNA template. Substitution of the asparagine at codon 348 in the p51 subunit with either isoleucine or leucine abrogated the observed protein-RNA interaction, thus, providing a possible explanation for the decreased RNase H phenotype. By contrast, alanine or glutamine substitutions exerted no effect. To validate this model, we introduced the N348I, N348L, N348A and N348Q mutations into RT and purified enzymes that contained subunit-specific mutations. N348I and N348L significantly decreased the frequency of secondary RNase H cleavages and increased the enzyme's ability to excise AZT-MP. As predicted by the modelling, this phenotype was due to the mutation in the p51 subunit of RT. By contrast, the N348A and N348Q RTs exhibited RNase H cleavage profiles and AZT-MP excision activities similar to the wild-type enzyme. All N348 mutant RTs exhibited decreased nevirapine susceptibility, although the N348I and N348L mutations conferred higher fold resistance values compared to N348A and N348Q. Nevirapine resistance was also largely due to the mutation present in the p51 subunit of RT.This study demonstrates that N348I-mediated AZT and nevirapine resistance is due to the mutation in the p51 subunit of RT.

Project description:ObjectivesAntiretroviral therapy (ART) efficacy is jeopardized by the emergence of drug resistance mutations in HIV, compromising treatment effectiveness. This study aims to propose novel analogs of Effavirenz (EFV) as potential direct inhibitors of HIV reverse transcriptase, employing computer-aided drug design methodologies.MethodsThree key approaches were applied: a mutational profile study, molecular dynamics simulations, and pharmacophore development. The impact of mutations on the stability, flexibility, function, and affinity of target proteins, especially those associated with NRTI, was assessed. Molecular dynamics analysis identified G190E as a mutation significantly altering protein properties, potentially leading to therapeutic failure. Comparative analysis revealed that among six first-line antiretroviral drugs, EFV exhibited notably low affinity with viral reverse transcriptase, further reduced by the G190E mutation. Subsequently, a search for EFV-similar inhibitors yielded 12 promising molecules based on their affinity, forming the basis for generating a pharmacophore model.ResultsMutational analysis pinpointed G190E as a crucial mutation impacting protein properties, potentially undermining therapeutic efficacy. EFV demonstrated diminished affinity with viral reverse transcriptase, exacerbated by the G190E mutation. The search for EFV analogs identified 12 high-affinity molecules, culminating in a pharmacophore model elucidating key structural features crucial for potent inhibition.ConclusionThis study underscores the significance of EFV analogs as potential inhibitors of HIV reverse transcriptase. The findings highlight the impact of mutations on drug efficacy, particularly the detrimental effect of G190E. The generated pharmacophore model serves as a pivotal reference for future drug development efforts targeting HIV, providing essential structural insights for the design of potent inhibitors based on EFV analogs identified in vitro.

Dataset Information

Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents.

Publications

Per-residue energy decomposition pharmacophore model to enhance virtual screening in drug discovery: a study for identification of reverse transcriptase inhibitors as potential anti-HIV agents.

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