Computational Chemistry Laboratory, Chemistry Department, Faculty of Science, Minia University, Minia, Egypt.
Chemistry of Medicinal Plants Department, National Research Centre, El-Tahrir St, Dokki, Giza, Egypt.
J Biomol Struct Dyn. 2021 Sep;39(15):5722-5734. doi: 10.1080/07391102.2020.1790037. Epub 2020 Jul 8.
In December 2019, a COVID-19 epidemic was discovered in Wuhan, China, and since has disseminated around the world impacting human health for millions. Herein, drug discovery approaches have been utilized to identify potential natural products (NPs) as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (M) inhibitors. The MolPort database that contains over 100,000 NPs was screened and filtered using molecular docking techniques. Based on calculated docking scores, the top 5,000 NPs/natural-like products (NLPs) were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. Combined 50 ns MD simulations and MM-GBSA calculations revealed nine potent NLPs with binding affinities (Δ) > -48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1,3]dioxolo)pyran-5-carboxamide derivatives showed Δ > -56.0 kcal/mol, forming essential short hydrogen bonds with HIS163 and GLY143 amino acids via dioxolane oxygen atoms. Structural and energetic analyses over 50 ns MD simulation demonstrated NLP-M complex stability. Drug-likeness predictions revealed the prospects of the identified NLPs as potential drug candidates. The findings are expected to provide a novel contribution to the field of COVID-19 drug discovery.Communicated by Ramaswamy H. Sarma.
2019 年 12 月，一种 COVID-19 疫情在中国武汉被发现，此后已在全球范围内传播，影响了数百万人的健康。在此，利用药物发现方法来鉴定潜在的天然产物（NPs）作为严重急性呼吸系统综合症冠状病毒 2（SARS-CoV-2）主要蛋白酶（M）抑制剂。利用分子对接技术筛选和过滤了 MolPort 数据库，该数据库包含超过 100,000 种 NPs。基于计算出的对接评分，选择了前 5,000 种 NPs/天然类似物（NLPs）进行分子动力学（MD）模拟，然后进行分子力学-广义 Born 表面积（MM-GBSA）结合能计算。50ns MD 模拟和 MM-GBSA 计算的组合结果显示，有 9 种具有结合亲和力（Δ）> -48.0kcal/mol 的强 NLPs。有趣的是，在所鉴定的 NLPs 中，有 4 种双（[1,3]二氧杂环戊烷-5-甲酰胺衍生物显示出 Δ> -56.0kcal/mol，通过二氧戊环氧原子与 HIS163 和 GLY143 氨基酸形成必需的短氢键。超过 50ns MD 模拟的结构和能量分析表明，NLP-M 复合物是稳定的。药物相似性预测显示，所鉴定的 NLPs 有望成为潜在的药物候选物。这些发现有望为 COVID-19 药物发现领域提供新的贡献。由 Ramaswamy H. Sarma 交流。
