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Current Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

Review Article

From Recognition to Reaction Mechanism: An Overview on the Interactions between HIV-1 Protease and its Natural Targets

Author(s): Monsurat M. Lawal, Zainab K. Sanusi, Thavendran Govender, Glenn E.M. Maguire, Bahareh Honarparvar and Hendrik G. Kruger*

Volume 27, Issue 15, 2020

Page: [2514 - 2549] Pages: 36

DOI: 10.2174/0929867325666181113122900

Price: $65

Abstract

Current investigations on the Human Immunodeficiency Virus Protease (HIV-1 PR) as a druggable target towards the treatment of AIDS require an update to facilitate further development of promising inhibitors with improved inhibitory activities. For the past two decades, up to 100 scholarly reports appeared annually on the inhibition and catalytic mechanism of HIV-1 PR. A fundamental literature review on the prerequisite of HIV-1 PR action leading to the release of the infectious virion is absent. Herein, recent advances (both computationally and experimentally) on the recognition mode and reaction mechanism of HIV-1 PR involving its natural targets are provided. This review features more than 80 articles from reputable journals. Recognition of the natural Gag and Gag-Pol cleavage junctions by this enzyme and its mutant analogs was first addressed. Thereafter, a comprehensive dissect of the enzymatic mechanism of HIV-1 PR on its natural polypeptide sequences from literature was put together. In addition, we highlighted ongoing research topics in which in silico methods could be harnessed to provide deeper insights into the catalytic mechanism of the HIV-1 protease in the presence of its natural substrates at the molecular level. Understanding the recognition and catalytic mechanism of HIV-1 PR leading to the release of an infective virion, which advertently affects the immune system, will assist in designing mechanismbased inhibitors with improved bioactivity.

Keywords: HIV-1 PR, natural substrates, recognition pattern, reaction mechanism, transition state modeling, immune system.

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