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基于 NCI 天然产物的 SARS-CoV-2 主蛋白酶抑制剂设计的计算研究。

Computational studies on the design of NCI natural products as inhibitors to SARS-CoV-2 main protease.

机构信息

School of Chemistry, University of Hyderabad, Hyderabad, India.

出版信息

J Biomol Struct Dyn. 2023 Jun;41(9):3741-3751. doi: 10.1080/07391102.2022.2054470. Epub 2022 Mar 25.

Abstract

The pandemic coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 5 million deaths globally. Currently there are no effective drugs available to treat COVID-19. The viral protease replication can be blocked by the inhibition of main protease that is encoded in polyprotein 1a and is therefore a potential protein target for drug discovery. We have carried out virtual screening of NCI natural compounds followed by molecular docking in order to identify hit molecules as probable SARS-CoV-2 main protease inhibitors. The molecular dynamics (MD) simulations of apo form in complex with N3, α-ketoamide and NCI natural products was used to validate the screened compounds. The MD simulations trajectories were analyzed using normal mode analysis and principal component analysis revealing dynamical nature of the protein. These findings aid in understanding the binding of natural products and molecular mechanisms of SARS-CoV-2 main protease inhibition.Communicated by Ramaswamy H. Sarma.

摘要

由严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2)引起的大流行性冠状病毒疾病(COVID-19)已在全球造成超过 500 万人死亡。目前尚无有效药物可用于治疗 COVID-19。病毒蛋白酶复制可通过抑制多蛋白 1a 中编码的主要蛋白酶来阻断,因此它是药物发现的潜在蛋白靶标。我们已经进行了 NCI 天然化合物的虚拟筛选,然后进行分子对接,以鉴定可能的 SARS-CoV-2 主要蛋白酶抑制剂的命中分子。使用无配体形式与 N3、α-酮酰胺和 NCI 天然产物复合物的分子动力学(MD)模拟来验证筛选出的化合物。使用正常模式分析和主成分分析对 MD 模拟轨迹进行分析,揭示了蛋白质的动力学性质。这些发现有助于理解天然产物的结合和 SARS-CoV-2 主要蛋白酶抑制的分子机制。由 Ramaswamy H. Sarma 传达。

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