针对SARS-COV2复制酶多蛋白1ab药物设计的植物源抗病毒化合物研究:硅方法

Areeba Shakeel, Bashah Javed
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引用次数: 0

摘要

Covid-19是由严重急性呼吸系统综合症(SARS)引起的,它导致全球数百万人死亡,因此确实有90多种疫苗被设计用于对抗它。在药物设计方面,我们采用了生物信息学技术,其靶标是covid-19的重要蛋白之一,即长7096个氨基酸,重794058个Da的复制多聚蛋白1ab,其重要结构域之一是宿主翻译抑制剂nsp1,通过与40S亚基的开头构象相关联来抑制宿主翻译。在本实验中,我们从各种药用植物中收集了50种抗病毒化合物的数据。将这些化合物与我们的目标,即病毒的蛋白质结合,进行对接。对接是通过使用MVD完成的,然后在Pymol上虚拟化化合物的3D结构。在得到所有结果后,选择对接分数最好的结果,即对接分数最低的化合物进行下一步的药物设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Plant-derived antiviral compounds study for drug designing against replicase polyprotein1ab of SARS-COV2: silico- approach
Covid-19 is caused by severe acute respiratory syndrome (SARS) and that leads to millions of death around the World so indeed there are over 90 vaccines are designed against it. For drug designing, we used Bioinformatics technology and the target is one of the important proteins of covid-19 i.e, Replication Poly- protein 1ab which is 7096 amino acids long and 794,058 Da in weight and one of its important domains is host translation inhibitor nsp1which inhibits host translation by associating with the open head conformation of the 40S subunit. For this experiment, we collected data of 50 antiviral compounds from various medicinal plants. Docking was performed with these compounds, combined with our target i.e, protein of the virus. Docking was done by using MVD followed by virtualization of the compound’s 3D structure on Pymol. After getting all the results, select the result having the best docking score that means compounds having the lowest docking score for further steps of drug designing.
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