Background

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.

Object

The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19.

Methods

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^pro) 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.

Results

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.

Conclusions

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.

中文翻译：

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筛选针对 SARS-CoV-2 蛋白酶及其两种亚洲突变体的强效植物化学抑制剂

背景

世界卫生组织于 2020 年 3 月宣布大流行的 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。该病毒已在全球造成超过 230 万人死亡。

目的

这项工作的主要目的是通过筛选天然产物库 (NPASS) 来研究可能治疗 COVID-19 的先导化合物。

方法

药效团特征用于筛选大型数据库以获得用于基于结构的天然产物化合物虚拟筛选的小型数据集。在基于结构的筛选中，进行分子对接以找到针对SARS-CoV-2的主要蛋白酶 (M ^{pro ) 的有效抑制剂分子 (PDB ID: 6Y7M)。}预测的先导化合物进一步进行分子动力学 (MD) 模拟，以检查先导化合物随时间演变的稳定性。

结果

在基于药效团的虚拟筛选中，在 30,927 种化合物中保留了 2,361 种化合物。在基于结构的筛选中，先导化合物根据其对接分数进行筛选。在 2,360 种化合物中，根据对接得分选择了 12 种先导化合物。具有 NPASS ID：NPC474104 的 Kazinol T 显示出最高的对接分数 -14.355，并通过了 Lipinski 的药物样参数标准。监测 ADMET 特性，Kazinol T 显示出其食用安全性。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。配体结合和未结合形式的蛋白酶及其突变体的正常模式分析揭示了 C-α 原子的位移和相关参数。

结论

天然产物 Kazinol T 是预测的针对 SARS-CoV-2 主要蛋白酶的先导化合物，将成为 COVID-19 的可能治疗方法。