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10.1080/07391102.2020.1772112

http://scihub22266oqcxt.onion/10.1080/07391102.2020.1772112
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32448034!7284142!32448034
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suck abstract from ncbi


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pmid32448034      J+Biomol+Struct+Dyn 2021 ; 39 (10): 3760-3770
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  • Identification of phytochemical inhibitors against main protease of COVID-19 using molecular modeling approaches #MMPMID32448034
  • Kumar A; Choudhir G; Shukla SK; Sharma M; Tyagi P; Bhushan A; Rathore M
  • J Biomol Struct Dyn 2021[Jul]; 39 (10): 3760-3770 PMID32448034show ga
  • Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel corona virus that causes corona virus disease 2019 (COVID-19). The COVID-19 rapidly spread across the nations with high mortality rate even as very little is known to contain the virus at present. In the current study, we report novel natural metabolites namely, ursolic acid, carvacrol and oleanolic acid as the potential inhibitors against main protease (M(pro)) of COVID-19 by using integrated molecular modeling approaches. From a combination of molecular docking and molecular dynamic (MD) simulations, we found three ligands bound to protease during 50 ns of MD simulations. Furthermore, the molecular mechanic/generalized/Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energy calculations showed that these chemical molecules have stable and favourable energies causing strong binding with binding site of M(pro) protein. All these three molecules, namely, ursolic acid, carvacrol and oleanolic acid, have passed the ADME (Absorption, Distribution, Metabolism, and Excretion) property as well as Lipinski's rule of five. The study provides a basic foundation and suggests that the three phytochemicals, viz. ursolic acid, carvacrol and oleanolic acid could serve as potential inhibitors in regulating the M(pro) protein's function and controlling viral replication. Communicated by Ramaswamy H. Sarma.
  • |Coronavirus 3C Proteases/*antagonists & inhibitors[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Phytochemicals/*pharmacology[MESH]
  • |Protease Inhibitors/*pharmacology[MESH]


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