选择抗病毒植物化学物质作为潜在的SARS-Cov-2主要蛋白酶抑制剂的计算评估:分子动力学引导的集合对接和扩展分子动力学

In Silico Pharmacology Pub Date : 2021-07-19 eCollection Date: 2021-01-01 DOI:10.1007/s40203-021-00107-9
Sanjay Sawant, Rajesh Patil, Manoj Khawate, Vishal Zambre, Vaibhav Shilimkar, Suresh Jagtap
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引用次数: 12

摘要

由新型冠状病毒引起的2019-nCoV或SARS-CoV-2已成为本世纪最严重的大流行。到目前为止,还没有治疗Covid-19的特异性疗法。最近,SARS-CoV-2潜在的药物靶点主要蛋白酶(Mpro)已成功结晶。本研究旨在通过集合对接、分子动力学和MM-PBSA计算,评估具有生物活性的抗病毒植物化学物质作为潜在的SARS-COV-2 Mpro抑制剂。使用Autodock vina程序进行整体对接研究。结合自由能最高的前5个化合物用Gromacs进行了100 ns分子动力学模拟。在MM-PBSA计算中进一步利用所得的MD收敛周期轨迹,得到了结合自由能的精确估计。对MD结果进行了RMSD、RMSF、氢键形成和占有参数的分析。以瑞德西韦和奈非那韦作为对照研究的标准药物。在对接研究中,发现五种植物化学物质,即大鼠黄素、阿门托黄酮、柚皮苷、扁桃黄酮和芦丁具有最低的结合自由能(-1),低于标准药物。MD研究表明,这五种植物化学物质与Mpro的配合物在公认的RMSD下稳定。其中,与标准药物瑞德西韦相比,扁柏黄酮类、阿门托黄酮类和柚皮苷类与ΔGbinging的结合亲和力更好。这些针对SARS-CoV-2的抑制剂的研究和验证将有助于将这些分子带到临床环境中。补充信息:在线版本包含补充资料,提供地址为10.1007/s40203-021-00107-9。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Computational assessment of select antiviral phytochemicals as potential SARS-Cov-2 main protease inhibitors: molecular dynamics guided ensemble docking and extended molecular dynamics.

Computational assessment of select antiviral phytochemicals as potential SARS-Cov-2 main protease inhibitors: molecular dynamics guided ensemble docking and extended molecular dynamics.

Computational assessment of select antiviral phytochemicals as potential SARS-Cov-2 main protease inhibitors: molecular dynamics guided ensemble docking and extended molecular dynamics.

Computational assessment of select antiviral phytochemicals as potential SARS-Cov-2 main protease inhibitors: molecular dynamics guided ensemble docking and extended molecular dynamics.

Covid-19 caused by novel coronavirus, 2019-nCoV or SARS-CoV-2 has become most severe pandemic of this century. No specific therapies are available to treat Covid-19 so far. Recently, main protease (Mpro), a potential drug target from SARS-CoV-2 has been successfully crystallised. The present study is aimed at assessment of bioactive antiviral phytochemicals as potential SARS-COV-2 Mpro inhibitors, using ensemble docking, molecular dynamics and MM-PBSA calculations. Ensemble docking studies were performed with Autodock vina program. The top 5 compounds having highest binding free energy were subjected to 100 ns molecular dynamics simulations with Gromacs. The resulting trajectories of converged period of MD were further exploited in MM-PBSA calculations to derive accurate estimates of binding free energies. The MD results were analysed with respect to RMSD, RMSF and hydrogen bond formation and occupancy parameters. The drugs remdesivir and nelfinavir were used as standard drugs for comparative studies. In the docking studies five phytochemicals, dalpanitin, amentoflavone, naringin, hinokiflavone, and rutin were found having lowest binding free energies (< - 10 kcal mol-1) which is lower than standard drugs. MD studies suggested that the complexes of these five phytochemicals with Mpro stabilize with well accepted RMSD. Amongst these phytochemicals, hinokiflavove, amentoflavone and naringin were found having better binding affinity with ΔGbinging than the standard drug remdesivir. Investigations and validation of these inhibitors against SARS-CoV-2 would be helpful in bring these molecules at the clinical settings.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-021-00107-9.

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