Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1102
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dc.contributor.authorBiswal, Bichitra K-
dc.contributor.authorJeyakanthan, Jeyaraman-
dc.contributor.authorKar, Deepsikha-
dc.contributor.authorTiwari, Satish-
dc.contributor.authorAhmad, Mohammed-
dc.contributor.authorDwivedy, Abhisek-
dc.contributor.authorMariadasse, Richard-
dc.date.accessioned2020-09-03T06:55:45Z-
dc.date.available2020-09-03T06:55:45Z-
dc.date.issued2020-07-
dc.identifier.urihttp://hdl.handle.net/123456789/1102-
dc.description.abstractThe current COVID-19 outbreak warrants the design and development of novel anti-COVID therapeutics. Using a combination of bioinformatics and computational tools, we modelled the 3D structure of the RdRp (RNA-dependent RNA polymerase) of SARS-CoV2 (severe acute respiratory syndrome coronavirus-2) and predicted its probable GTP binding pocket in the active site. GTP is crucial for the formation of the initiation complex during RNA replication. This site was computationally targeted using a number of small molecule inhibitors of the hepatitis C RNA polymerase reported previously. Further optimizations suggested a lead molecule that may prove fruitful in the development of potent inhibitors against the RdRp of SARS-CoV2en_US
dc.language.isoenen_US
dc.publisherAmerican Chemical Societyen_US
dc.titlePrediction of Small Molecule Inhibitors Targeting the Severe Acute Respiratory Syndrome Coronavirus-2 RNA-dependent RNA Polymeraseen_US
dc.journalACS Omegaen_US
dc.volumeno5en_US
dc.issueno29en_US
dc.pages18356-18366en_US
Appears in Collections:Protein Crystallography, Publications

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