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In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis.
Nagar, Prinsa R; Gajjar, Normi D; Dhameliya, Tejas M.
Afiliação
  • Nagar PR; L. M. College of Pharmacy, Navrangpura, Ahmedabad, Gujarat 380009, India.
  • Gajjar ND; L. M. College of Pharmacy, Navrangpura, Ahmedabad, Gujarat 380009, India.
  • Dhameliya TM; L. M. College of Pharmacy, Navrangpura, Ahmedabad, Gujarat 380009, India.
J Mol Struct ; 1246: 131190, 2021 Dec 15.
Article em En | MEDLINE | ID: mdl-34334813
Severe acute respiratory syndrome has relapsed recently as novel coronavirus causing a life threat to the entire world in the absence of an effective therapy. To hamper the replication of the deadly SARS CoV-2 inside the host cells, systematic in silico virtual screening of total 267,324 ligands from Asinex EliteSynergy and BioDesign libraries has been performed using AutoDock Vina against RdRp. The molecular modeling studies revealed the identification of twenty-one macrocyclic hits (2-22) with better binding energy than remdesivir (1), marketed SARS CoV-2 inhibitor. Further, the analysis using rules for drug-likeness and their ADMET profile revealed the candidature of these hits due to superior oral bioavailability and druggability. Further, the MD simulation studies of top two hits (2 and 3) performed using GROMACS 2020.1 for 10 ns revealed their stability into the docked complexes. These results provide an important breakthrough in the design of macrocyclic hits as SARS CoV-2 RNA replicase inhibitor.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article