Title of article
Computational proteomics analysis of binding mechanisms and molecular signatures of the HIV-1 protease drugs
Author/Authors
Verkhivker، نويسنده , , Gennady، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2009
Pages
10
From page
197
To page
206
Abstract
SummaryObjective
ational proteomics analysis of biomolecular interactions is proposed to determine molecular signatures of the HIV-1 protease inhibitors. A comparative microscopic analysis is conducted for a panel of inhibitors which exemplify a diversity of the HIV-1 PR binding mechanisms, from the active site inhibition to intervening with the protease folding and dimerization.
s and materials
a-exchange Monte Carlo simulations with the conformational ensembles of the HIV-1 PR dimer and monomer structures enable a molecular analysis underlying diversity of the HIV-1 PR binding mechanisms.
s
e investigated the molecular basis underlying diversity of the HIV-1 PR binding mechanisms. The molecular basis of the HIV-1 PR active site and dimerization inhibition mechanisms has been analyzed for an active site tripeptide inhibitor and a tetrapeptide inhibitor, which can act as both a dimerization inhibitor and a competitive active site inhibitor. We have also simulated a structural mimicry mechanism of the HIV-1 PR folding inhibition and dimerization, according to which the folding inhibitor targets the conserved HIV-1 PR regions by mimicking the interaction network of the active dimer.
sions
e shown that binding interfaces of the studied dimerization and folding HIV-1 PR inhibitors may enable structural mimicry with the hot spot residues of the HIV-1 PR dimer. The proposed structural models of intervening with the HIV-1 PR dimerization and folding support the mechanism of structural mimicry, which may alleviate drug resistance effects.
Keywords
Folding inhibition , Drug resistance , Structural mimicry , HIV-1 protease , Monte Carlo simulations , Dimerization inhibitors
Journal title
Artificial Intelligence In Medicine
Serial Year
2009
Journal title
Artificial Intelligence In Medicine
Record number
1835115
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