Author: Azad, Iqbal; Khan, Tahmeena; Maurya, Akhilesh Kumar; Irfan Azad, Mohd.; Mishra, Nidhi; Alanazi, Amer M.
Title: Identification of Severe Acute Respiratory Syndrome Coronavirusâ€2 inhibitors through in silico structureâ€based virtual screening and molecular interaction studies Cord-id: 0bj1asxg Document date: 2021_6_15
ID: 0bj1asxg
Snippet: The novel coronavirus Severe Acute Respiratory Syndrome Coronavirusâ€2 (SARSâ€CoVâ€2) or COVIDâ€19 has caused a worldwide pandemic. The fatal virus has affected the health of human beings as well as the socioâ€economic situation all over the world. To date, no concrete medicinal solution has been proposed to combat the viral infection, calling for an urgent, strategic, and costâ€effective drug development approach that may be achievable by applying targeted computational and virtual screen
Document: The novel coronavirus Severe Acute Respiratory Syndrome Coronavirusâ€2 (SARSâ€CoVâ€2) or COVIDâ€19 has caused a worldwide pandemic. The fatal virus has affected the health of human beings as well as the socioâ€economic situation all over the world. To date, no concrete medicinal solution has been proposed to combat the viral infection, calling for an urgent, strategic, and costâ€effective drug development approach that may be achievable by applying targeted computational and virtual screening protocols. Immunity is the body's natural defense against diseaseâ€causing pathogens, which can be boosted by consuming plantâ€based or natural food products. Active constituents derived from natural sources also scavenge the free radicals and have antiâ€inflammatory activities. Herbs and spices have been used for various medicinal purposes. In this study, 2,96 365 natural and synthetic derivatives (ligands) belonging to 102 classes of compounds were obtained from PubChem and assessed on Lipinski's parameters for their potential bioavailability. Out of all the derivatives, 3254 obeyed Lipinski's rule and were virtually screened. The 115 top derivatives were docked against SARSâ€CoVâ€2, SARSâ€CoV, MERSâ€CoV, and HCoVâ€HKV1 main proteases (M(pro)s) as receptors using AutoDock Vina, AutoDock, and iGEMDOCK 2.1. The lowest binding energy was exhibited by ligands 2 and 6 against all the four M(pro)s. The molecular dynamic simulation was also performed with ligand 6 using the GROMACS package. Good bioactivity scores, absorption, distribution, metabolism, excretion, and toxicity profile and drugâ€like pharmacokinetic parameters were also obtained. Hydroxychloroquine was used as the control drug.
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