Premium
In Silico Investigation of a HIV‐1 Vpr Inhibitor Binding Site: Potential for Virtual Screening and anti‐HIV Drug Design
Author(s) -
Choi Sy Bing,
Choong Yee Siew,
Saito Akiko,
Wahab Habibah A.,
Najimudin Nazalan,
Watanabe Nobumoto,
Osada Hiroyuki,
Ong Eugene Boon Beng
Publication year - 2014
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201400080
Subject(s) - virtual screening , in silico , docking (animal) , homology modeling , binding site , computational biology , human immunodeficiency virus (hiv) , binding pocket , drug discovery , mutant , chemistry , plasma protein binding , drug , small molecule , biology , biochemistry , enzyme , virology , gene , pharmacology , medicine , nursing
Present HIV antiviral therapy only targets structural proteins of HIV, but evidence shows that the targeting of accessory proteins will expand our options in combating HIV. HIV‐1 Vpr, a multifunctional accessory protein involved in viral infection, replication and pathogenesis, is a potential target. Previously, we have shown that phenyl coumarin compounds can inhibit the growth arrest activity of Vpr in host cells and predicted that the inhibitors’ binding site is a hydrophobic pocket on Vpr. To investigate our prediction of the inhibitors’ binding site, we docked the coumarin inhibitors into the predicted hydrophobic binding pocket on a built model of Vpr and observed a linear trend between their calculated binding energies and prior experimentally determined potencies. Subsequently, to analyze the inhibitor‐protein binding interactions in detail, we built homology models of Vpr mutants and performed docking studies on these models too. The results revealed that structural changes on the binding pocket that were caused by the mutations affected inhibitor binding. Overall, this study showed that the binding energies of the docked molecules are good indicators of the activity of the inhibitors. Thus, the model can be used in virtual screening to identify other Vpr inhibitors and for designing more potent inhibitors.