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ChemMedChem . Targeting SARS-CoV-2 RBD interface: a supervised computational data-driven approach to identify potential modulators

tetano

Editor, Senior Moderator
ChemMedChem


. 2020 Jul 23.
doi: 10.1002/cmdc.202000259. Online ahead of print.
Targeting SARS-CoV-2 RBD interface: a supervised computational data-driven approach to identify potential modulators


Maria Rita Gulotta[SUP] 1 [/SUP], Jessica Lombino[SUP] 1 [/SUP], Ugo Perricone[SUP] 2 [/SUP], Giada De Simone[SUP] 1 [/SUP], Nedra Mekni[SUP] 1 [/SUP], Maria De Rosa[SUP] 1 [/SUP], Patrizia Diana[SUP] 3 [/SUP], Alessandro Padova[SUP] 1 [/SUP]



Affiliations

Abstract

Coronavirus Disease 2019 (COVID-19) has spread out as a pandemic threat affecting over 2 million people. The infectious process initiates via binding of SARS-CoV-2 Spike (S) glycoprotein to host Angiotensin-converting enzyme 2 (ACE2). The interaction is mediated by the receptor-binding domain (RBD) of S glycoprotein, promoting host receptor recognition and binding to ACE2 peptidase domain (PD), thus representing a promising target for therapeutic intervention. Herein, we present a computational study aimed at identifying small molecules potentially able to target RBD. Although targeting PPI remains a challenge in drug discovery, our investigation highlights that interaction between SARS-CoV-2 RBD and ACE2 PD might be prone to small molecule modulation, due to the hydrophilic nature of the bi-molecular recognition process and the presence of druggable hot spots. The fundamental objective is to identify, and provide to the international scientific community, hit molecules potentially suitable to enter the drug discovery process, preclinical validation and development.

Keywords: COVID-19; Molecular dynamics; Pharmacophore; Protein-Protein Interaction; docking.
 
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