Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey.
Computational Science and Engineering Division, Informatics Institute, Istanbul Technical University, Istanbul, Turkey.
Proteins. 2021 Nov;89(11):1425-1441. doi: 10.1002/prot.26164. Epub 2021 Jul 5.
The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has serious negative effects on health, social life, and economics. Recently, vaccines from various companies have been urgently approved to control SARS-CoV-2 infections. However, any specific antiviral drug has not been confirmed so far for regular treatment. An important target is the main protease (M ), which plays a major role in replication of the virus. In this study, Gaussian and residue network models are employed to reveal two distinct potential allosteric sites on M that can be evaluated as drug targets besides the active site. Then, Food and Drug Administration (FDA)-approved drugs are docked to three distinct sites with flexible docking using AutoDock Vina to identify potential drug candidates. Fourteen best molecule hits for the active site of M are determined. Six of these also exhibit high docking scores for the potential allosteric regions. Full-atom molecular dynamics simulations with MM-GBSA method indicate that compounds docked to active and potential allosteric sites form stable interactions with high binding free energy (∆G ) values. ∆G values reach -52.06 kcal/mol for the active site, -51.08 kcal/mol for the potential allosteric site 1, and - 42.93 kcal/mol for the potential allosteric site 2. Energy decomposition calculations per residue elucidate key binding residues stabilizing the ligands that can further serve to design pharmacophores. This systematic and efficient computational analysis successfully determines ivermectine, diosmin, and selinexor currently subjected to clinical trials, and further proposes bromocriptine, elbasvir as M inhibitor candidates to be evaluated against SARS-CoV-2 infections.
新型冠状病毒病 2019(COVID-19)是由严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2)引起的,它仍然对健康、社会生活和经济造成严重的负面影响。最近,多家公司的疫苗已被紧急批准用于控制 SARS-CoV-2 感染。然而,迄今为止,尚未有任何特定的抗病毒药物被证实可用于常规治疗。一个重要的靶点是主要蛋白酶(M),它在病毒的复制中起着主要作用。在这项研究中,我们使用高斯和残基网络模型揭示了 M 上两个独特的潜在变构位点,除了活性位点之外,这两个变构位点也可以作为药物靶点进行评估。然后,我们使用 AutoDock Vina 对三个不同的位点进行柔性对接,对接经食品和药物管理局(FDA)批准的药物,以鉴定潜在的药物候选物。确定了 14 种针对 M 的活性位点的最佳分子命中物。其中有 6 种对潜在变构区域也表现出较高的对接评分。使用 MM-GBSA 方法的全原子分子动力学模拟表明,对接至活性和潜在变构位点的化合物与具有高结合自由能(∆G)值的稳定相互作用。∆G 值分别达到-52.06 kcal/mol(活性位点)、-51.08 kcal/mol(潜在变构位点 1)和-42.93 kcal/mol(潜在变构位点 2)。每个残基的能量分解计算阐明了稳定配体的关键结合残基,这些残基可以进一步用于设计药效团。这种系统和有效的计算分析成功地确定了伊维菌素、地奥司明和塞利尼索,它们目前正在进行临床试验,并进一步提出了溴隐亭、Elbasvir 作为 M 抑制剂候选物,以评估它们对 SARS-CoV-2 感染的疗效。