School of Pharmacy, Jiangsu Vocational College of Medicine, Yancheng 224005, China.
Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Molecules. 2023 Jan 17;28(3):937. doi: 10.3390/molecules28030937.
The transmission and infectivity of COVID-19 have caused a pandemic that has lasted for several years. This is due to the constantly changing variants and subvariants that have evolved rapidly from SARS-CoV-2. To discover drugs with therapeutic potential for COVID-19, we focused on the 3CL protease (3CL) of SARS-CoV-2, which has been proven to be an important target for COVID-19 infection. Computational prediction techniques are quick and accurate enough to facilitate the discovery of drugs against the 3CL of SARS-CoV-2. In this paper, we used both ligand-based virtual screening and structure-based virtual screening to screen the traditional Chinese medicine small molecules that have the potential to target the 3CL of SARS-CoV-2. MD simulations were used to confirm these results for future in vitro testing. MCCS was then used to calculate the normalized free energy of each ligand and the residue energy contribution. As a result, we found ZINC15676170, ZINC09033700, and ZINC12530139 to be the most promising antiviral therapies against the 3CL of SARS-CoV-2.
COVID-19 的传播和传染性导致了一场持续多年的大流行。这是由于 SARS-CoV-2 不断变化的变体和亚变体迅速进化所致。为了发现具有治疗 COVID-19 潜力的药物,我们专注于 SARS-CoV-2 的 3CL 蛋白酶(3CL),事实证明,它是 COVID-19 感染的重要靶点。计算预测技术快速准确,足以促进针对 SARS-CoV-2 的 3CL 的药物发现。在本文中,我们使用配体基础虚拟筛选和基于结构的虚拟筛选来筛选具有靶向 SARS-CoV-2 3CL 潜力的中药小分子。MD 模拟用于确认这些结果,以便将来进行体外测试。然后使用 MCCS 计算每个配体的归一化自由能和残基能量贡献。结果表明,ZINC15676170、ZINC09033700 和 ZINC12530139 是针对 SARS-CoV-2 3CL 的最有希望的抗病毒疗法。