Identification of Severe Acute Respiratory Syndrome Coronavirus-2 inhibitors through in silico structure-based virtual screening and molecular interaction studies

通过基于计算机结构的虚拟筛选和分子相互作用研究鉴定严重急性呼吸综合征冠状病毒2抑制剂

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Abstract

The novel coronavirus Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 has caused a worldwide pandemic. The fatal virus has affected the health of human beings as well as the socio-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 cost-effective drug development approach that may be achievable by applying targeted computational and virtual screening protocols. Immunity is the body's natural defense against disease-causing pathogens, which can be boosted by consuming plant-based or natural food products. Active constituents derived from natural sources also scavenge the free radicals and have anti-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 SARS-CoV-2, SARS-CoV, MERS-CoV, and HCoV-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 drug-like pharmacokinetic parameters were also obtained. Hydroxychloroquine was used as the control drug.

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