ChemRxiv · 2020 · 31 citations · 28 references
PharmacyMedicinal ChemistryPharmacologyDrug DesignDrug DiscoveryLead OptimizationComputational Drug DiscoveryComputational Drug RepurposingEnzyme InhibitionStructure-based RepurposingVirtual ScreeningComputer-aided Drug DiscoveryInhibitor ScreeningStructure-based ScreeningVirtual Screening Filters
In this work, computer-aided drug design method has been implemented to quickly identify promising drug repurposing candidates against COVID-19 main protease (M pro ) . The world is facing an epidemic and in absence of vaccine or any effective treatment, it has created a sense of urgency for novel drug discovery approaches. We have made an immediate effort by performing virtual screening of clinically approved drugs or molecules under clinical trials against COVID-19 M pro to identify potential drug molecules. With given knowledge of this system, N3 and 13B compounds have shown inhibitory effect against COVID-19 M pro . Both the compounds were considered as control to filter out the screened molecules. Overall, we have identified six potential compounds, Leupeptin Hemisulphate, Pepstatin A, Nelfinavir , Birinapant, Lypression and Octeotide which have shown the docking energy > -8.0 kcal/mol and MMGBSA > -68.0 kcal/mol. The binding pattern of these compounds suggests that they interacted with key hot-spot residues. Also, their pharmacokinetic annotations and therapeutic importance have indicated that they possess drug-like properties and could pave their way for in-vitro studies. The findings of this work will be significant for structure and pharmacophore-based designing.
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VMD: Visual molecular dynamics
William Humphrey, Andrew Dalke, Klaus Schulten · Journal of Molecular Graphics · 1996 · 66.6K citations
Features, Evaluation and Treatment Coronavirus (COVID-19)
Marco Cascella, Michael Rajnik, Arturo Cuomo et al. · StatPearls · 2020 · 3.3K citations