Department of Zoology, Abdul Wali Khan University Mardan, 23200, Pakistan.
Department of Biochemistry, Abdul Wali Khan University Mardan, 23200, Pakistan.
Comput Biol Med. 2021 Jun;133:104362. doi: 10.1016/j.compbiomed.2021.104362. Epub 2021 Apr 16.
COVID-19, declared a pandemic in March 2020 by the World Health Organization is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The virus has already killed more than 2.3 million people worldwide.
The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19.
Pharmacophore features were used to screen a large database to get a small dataset for structure-based virtual screening of natural product compounds. In the structure-based screening, molecular docking was performed to find a potent inhibitor molecule against the main protease (M) of SARS-CoV-2 (PDB ID: 6Y7M). The predicted lead compound was further subjected to Molecular Dynamics (MD) simulation to check the stability of the leads compound with the evolution of time.
In pharmacophore-based virtual screening, 2,361 compounds were retained out of 30,927. In the structure-based screening, the lead compounds were filtered based on their docking scores. Among the 2,360 compounds, 12 lead compounds were selected based on their docking score. Kazinol T with NPASS ID: NPC474104 showed the highest docking score of -14.355 and passed criteria of Lipinski's drug-like parameters. Monitoring ADMET properties, Kazinol T showed its safety for consumption. Docking of Kazinol T with two Asian mutants (R60C and I152V) showed variations in binding and energy parameters. Normal mode analysis for ligand-bound and unbound form of protease along with its mutants, revealed displacement and correlation parameters for C-alpha atoms. MD simulation results showed that all ligand-protein complexes remained intact and stable in a dynamic environment with negative Gibbs free energy.
The natural product Kazinol T was a predicted lead compound against the main protease of SARS-CoV-2 and will be the possible treatment for COVID-19.
2020 年 3 月，世界卫生组织宣布 COVID-19 为大流行疾病，其由严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2）引起。该病毒已在全球范围内导致超过 230 万人死亡。
本研究旨在通过筛选天然产物库（NPASS）寻找针对 COVID-19 的潜在治疗方法，以寻找先导化合物。
利用药效基团特征筛选大型数据库，得到一个小数据集，用于基于结构的天然产物化合物虚拟筛选。在基于结构的筛选中，对 SARS-CoV-2 的主要蛋白酶（M）进行分子对接（PDB ID：6Y7M），以寻找有效的抑制剂分子。预测的先导化合物进一步进行分子动力学（MD）模拟，以检查随着时间的推移先导化合物的稳定性。
在基于药效基团的虚拟筛选中，从 30927 个化合物中保留了 2361 个化合物。在基于结构的筛选中，根据对接评分筛选出先导化合物。在 2360 种化合物中，根据对接评分选择了 12 种先导化合物。天然产物 NPC474104（Kazinol T）的对接评分为-14.355，得分最高，符合 Lipinski 的类药性参数标准。监测 ADMET 特性，Kazinol T 显示出其可安全使用。Kazinol T 与两个亚洲突变体（R60C 和 I152V）的对接显示出结合和能量参数的变化。配体结合和非结合形式的蛋白酶及其突变体的正常模式分析显示了 C-α 原子的位移和相关性参数。MD 模拟结果表明，在动态环境中，所有配体-蛋白复合物均保持完整和稳定，吉布斯自由能为负值。
天然产物 Kazinol T 是针对 SARS-CoV-2 主要蛋白酶的预测先导化合物，可能成为 COVID-19 的治疗方法。
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