Department of Biotechnology, Kumaun University, Bhimtal, Uttarakhand, India.
Department of Botany, Kumaun University, S.S.J Campus, Almora, Uttarakhand, India.
J Biomol Struct Dyn. 2022 Feb;40(3):1084-1100. doi: 10.1080/07391102.2020.1821785. Epub 2020 Sep 17.
The sudden outbreak of COVID-19 has been responsible for several deaths across the globe. Due to its high contagious nature, it spreads from one human to another very quickly. Now it becomes a global public health threat with no approved treatments. In silico techniques can accelerate the drug development process. Our research aimed to identify the novel drugs for inhibition of Main protease (Mpro) enzyme of COVID-19 by performing in silico approach. In this context, a library consisting of 3180 FDA-approved drugs from 'the ZINC database' was used to identify novel drug candidates against 'the Mpro' of SARS-CoV-2. Initially, the top 10 drugs out of 3180 drugs were selected by molecular docking according to their binding score. Among 10 selected drugs; seven drugs that showed binding with Mpro enzyme residue Glu166 were subjected to100 ns Molecular dynamics (MD) simulation. Out of seven compounds, four namely, ZINC03831201, ZINC08101052, ZINC01482077, and ZINC03830817 were found significant based on MD simulation results. Furthermore, RMSD, RMSF, RG, SASA, PCA, MMPBSA (for last 40 ns) were calculated for the 100 ns trajectory period. Currently, the world needs potent drugs in a short period and this work suggests that these four drugs could be used as novel drugs against COVID-19 and it also provides new lead compounds for further in vitro, in vivo, and ongoing clinical studies against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.
新型冠状病毒肺炎（COVID-19）的突然爆发已在全球范围内导致了数人死亡。由于其高度传染性，它在人与人之间传播得非常快。现在，它已成为一种没有经过批准的治疗方法的全球公共卫生威胁。计算机技术可以加速药物开发过程。我们的研究旨在通过计算机方法鉴定新型药物，以抑制 COVID-19 的主要蛋白酶（Mpro）酶。在此背景下，从“ZINC 数据库”中使用了包含 3180 种美国食品和药物管理局批准的药物的库，以鉴定针对 SARS-CoV-2 的“Mpro”的新型药物候选物。最初，根据结合评分，从 3180 种药物中选择前 10 种药物进行分子对接。在这 10 种选定的药物中；有 7 种药物与 Mpro 酶残基 Glu166 结合，然后进行 100ns 分子动力学（MD）模拟。在这 7 种化合物中，有 4 种化合物，即 ZINC03831201、ZINC08101052、ZINC01482077 和 ZINC03830817，根据 MD 模拟结果发现它们具有显著的结合能力。此外，还对 100ns 轨迹期的 RMSD、RMSF、RG、SASA、PCA 和 MMPBSA（最后 40ns）进行了计算。目前，全世界都需要在短时间内获得有效的药物，这项工作表明，这四种药物可作为治疗 COVID-19 的新型药物，也为进一步的体外、体内和正在进行的针对 SARS-CoV-2 的临床研究提供了新的先导化合物。Ramaswamy H. Sarma 通讯。
