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• W3166104600 abstract "COVID-19, the current global pandemic has caused immense damage to human lives and the global economy. It is instigated by the SARS-CoV-2 virus and there is an immediate need for the identification of effective drugs against this deadly virus. SARS-CoV-2 genome codes for four structural proteins, sixteen non-structural proteins (NSPs) and several accessory proteins for its survival inside the host cells. In the present study, through in silico approaches, we aim to identify compounds that are effective against the four NSPs namely, NSP1, NSP4, NSP6 and NSP13 of SARS-CoV-2. The selection criteria of these four NSP proteins are they are least explored and potential targets. First, we have modeled the 3D structures of these proteins using homology modeling methods. Further, through molecular docking studies, we have screened the FDA-approved compounds against these modeled proteins and reported their docking scores. To gain dynamic insights, molecular dynamics studies have also been carried out for the best scored ligand against the NSPs. This study can further pave way for exposing more number of compounds against these proteins and enhance COVID-19 treatment.The online version contains supplementary material available at 10.1007/s42485-021-00067-w." @default.
• W3166104600 created "2021-06-22" @default.
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• W3166104600 date "2021-06-09" @default.
• W3166104600 modified "2023-10-15" @default.
• W3166104600 title "Screening of FDA-approved compound library identifies potential small-molecule inhibitors of SARS-CoV-2 non-structural proteins NSP1, NSP4, NSP6 and NSP13: molecular modeling and molecular dynamics studies" @default.
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• W3166104600 doi "https://doi.org/10.1007/s42485-021-00067-w" @default.
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