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In silico prediction of natural compounds as potential multi-target inhibitors of structural proteins of SARS-CoV-2.


ABSTRACT: 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.

SUBMITTER: Rani J 

PROVIDER: S-EPMC8425474 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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<i>In silico</i> prediction of natural compounds as potential multi-target inhibitors of structural proteins of SARS-CoV-2.

Rani Jyoti J   Bhargav Anasuya A   Khan Faez Iqbal FI   Ramachandran Srinivasan S   Lai Dakun D   Bajpai Urmi U  

Journal of biomolecular structure & dynamics 20210906 22


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  ...[more]

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