| Literature DB >> 33774182 |
Ibrahim Damilare Boyenle1, Ukachi Chiamaka Divine1, Rofiat Adeyemi1, Kehinde Sulaimon Ayinde2, Olamide Tosin Olaoba3, Chowdhry Apu4, Lei Du5, Qian Lu5, Xiaoxing Yin5, Temitope Isaac Adelusi6.
Abstract
The recent outcry in the search for direct keap1 inhibitors requires a quicker and more effective drug discovery process which is an inherent property of the Computer Aided Drug Discovery (CADD) to bring drug candidates into the clinic for patient's use. This Keap1 (negative regulator of ARE master activator) is emerging as a therapeutic strategy to combat oxidative stress-orchestrated diseases. The advances in computer algorithm and compound databases require that we highlight the functionalities that this technology possesses that can be exploited to target Keap1-Nrf2 PPI. Therefore, in this review, we uncover the in silico approaches that had been exploited towards the identification of keap1 inhibition in the light of appropriate fitting with relevant amino acid residues, we found 3 and 16 other compounds that perfectly fit keap1 kelch pocket/domain. Our goal is to harness the parameters that could orchestrate keap1 surface druggability by utilizing hotspot regions for virtual fragment screening and identification of hotspot residues.Entities:
Keywords: Computer Aided Drug Design (CADD); In silico; Keap1; Oxidative stress; Protein-protein interaction (PPI)
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Year: 2021 PMID: 33774182 DOI: 10.1016/j.phrs.2021.105577
Source DB: PubMed Journal: Pharmacol Res ISSN: 1043-6618 Impact factor: 7.658