Titel
A Computational Approach to Identify Potential Novel Inhibitors against the Coronavirus SARS‐CoV‐2
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Abstract
The current pandemic threat of COVID-19, caused by the novel coronavirus SARS-CoV-2, not only gives rise to a high number of deaths around the world but also has immense consequences for the worldwide health systems and global economy. Given the fact that this pandemic is still ongoing and there are currently no drugs or vaccines against this novel coronavirus available, this in silico study was conducted to identify a potential novel SARS-CoV-2-inhibitor. Two different approaches were pursued: 1) The Docking Consensus Approach (DCA) is a novel approach, which combines molecular dynamics simulations with molecular docking. 2) The Common Hits Approach (CHA) in contrast focuses on the combination of the feature information of pharmacophore modeling and the flexibility of molecular dynamics simulations. The application of both methods resulted in the identification of 10 compounds with high coronavirus inhibition potential.
Stichwort
COVID-19coronavirusvirtual screeningin silicomolecular dockingcommon hits approachdocking consensus approach
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
https://phaidra.univie.ac.at/o:1219320
Erschienen in
Titel
Molecular Informatics
Band
39
Ausgabe
10
ISSN
1868-1743
Erscheinungsdatum
2020
Verlag
Wiley
Erscheinungsdatum
2020
Zugänglichkeit
Rechteangabe
© 2020 The Authors

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