Foundation University Medical College, Foundation University Islamabad, DHA-I, Islamabad 44000, Pakistan.
Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan.
Molecules. 2021 Mar 7;26(5):1446. doi: 10.3390/molecules26051446.
With the emergence and global spread of the COVID-19 pandemic, the scientific community worldwide has focused on search for new therapeutic strategies against this disease. One such critical approach is targeting proteins such as helicases that regulate most of the SARS-CoV-2 RNA metabolism. The purpose of the current study was to predict a library of phytochemicals derived from diverse plant families with high binding affinity to SARS-CoV-2 helicase (Nsp13) enzyme. High throughput virtual screening of the Medicinal Plant Database for Drug Design (MPD3) database was performed on SARS-CoV-2 helicase using AutoDock Vina. Nilotinib, with a docking value of -9.6 kcal/mol, was chosen as a reference molecule. A compound (PubChem CID: 110143421, ZINC database ID: ZINC257223845, eMolecules: 43290531) was screened as the best binder (binding energy of -10.2 kcal/mol on average) to the enzyme by using repeated docking runs in the screening process. On inspection, the compound was disclosed to show different binding sites of the triangular pockets collectively formed by Rec1A, Rec2A, and 1B domains and a stalk domain at the base. The molecule is often bound to the ATP binding site (referred to as binding site 2) of the helicase enzyme. The compound was further discovered to fulfill drug-likeness and lead-likeness criteria, have good physicochemical and pharmacokinetics properties, and to be non-toxic. Molecular dynamic simulation analysis of the control/lead compound complexes demonstrated the formation of stable complexes with good intermolecular binding affinity. Lastly, affirmation of the docking simulation studies was accomplished by estimating the binding free energy by MMPB/GBSA technique. Taken together, these findings present further in silco investigation of plant-derived lead compounds to effectively address COVID-19.
随着 COVID-19 大流行的出现和在全球范围内的传播，全世界的科学界都专注于寻找针对这种疾病的新治疗策略。其中一种关键方法是针对调节大多数 SARS-CoV-2 RNA 代谢的蛋白质，例如解旋酶。本研究的目的是预测来自不同植物科的具有与 SARS-CoV-2 解旋酶（Nsp13）酶高结合亲和力的植物化学物质文库。使用 AutoDock Vina 对 Medicinal Plant Database for Drug Design（MPD3）数据库进行了针对 SARS-CoV-2 解旋酶的高通量虚拟筛选。尼洛替尼的对接值为-9.6 kcal/mol，被选为参考分子。在筛选过程中，通过重复对接运行，筛选出一种化合物（PubChem CID：110143421，ZINC 数据库 ID：ZINC257223845，eMolecules：43290531）作为与酶的最佳结合物（平均结合能为-10.2 kcal/mol）。经检查，该化合物被披露显示出不同的结合位点，这些结合位点由 Rec1A、Rec2A 和 1B 结构域以及基部的茎结构域共同形成的三角形口袋。该分子通常与解旋酶酶的 ATP 结合位点（称为结合位点 2）结合。进一步发现该化合物满足药物样和铅样标准，具有良好的物理化学和药代动力学性质，并且无毒。对照/先导化合物复合物的分子动力学模拟分析表明，形成了具有良好分子间结合亲和力的稳定复合物。最后，通过 MMPB/GBSA 技术估计结合自由能来验证对接模拟研究。总之，这些发现为进一步研究植物来源的先导化合物以有效应对 COVID-19 提供了依据。
