Author: Rani, Jyoti; Bhargav, Anasuya; Khan, Faez Iqbal; Ramachandran, Srinivasan; Lai, Dakun; Bajpai, Urmi
Title: In silico prediction of natural compounds as potential multi-target inhibitors of structural proteins of SARS-CoV-2 Cord-id: 00cbc8gl Document date: 2021_9_6
ID: 00cbc8gl
Snippet: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a colossal loss to human health and lives and has deeply impacted socio-economic growth. Remarkable efforts have been made by the scientific community in containing the virus by successful development of vaccines and diagnostic kits. Initiatives towards drug repurposing and discovery have also been undertaken. In this study, we compiled the known natural anti-viral compounds using text mining of the literature and examin
Document: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a colossal loss to human health and lives and has deeply impacted socio-economic growth. Remarkable efforts have been made by the scientific community in containing the virus by successful development of vaccines and diagnostic kits. Initiatives towards drug repurposing and discovery have also been undertaken. In this study, we compiled the known natural anti-viral compounds using text mining of the literature and examined them against four major structural proteins of SARS-CoV-2, namely, spike (S) protein, nucleocapsid (N) protein, membrane (M) protein and envelope (E) protein. Following computational approaches, we identified fangchinoline and versicolactone C as the compounds to exhibit strong binding to the target proteins and causing structural deformation of three structural proteins (N, S and M). We recommend the inhibitory effects of these compounds from our study should be experimentally validated against SARS-CoV-2. Communicated by Ramaswamy H. Sarma
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