Suppr超能文献

用合成/设计的非天然核苷类似物靶向严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的RNA依赖性RNA聚合酶(RdRp):一项计算机模拟研究

Targeting the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) with synthetic/designer unnatural nucleoside analogs: an in silico study.

作者信息

Bag Subhendu Sekhar, Sinha Sayantan, Dutta Soumya, Baishya Hirak Jyoti, Paul Suravi

机构信息

Chemical Biology/Genomics Laboratory, Department of Chemistry, Indian Institute of Technology Guwahati, Guwahati, Assam, India, 781039.

Centre for the Environment, Indian Institute of Technology Guwahati, Guwahati, Assam, India, 781039.

出版信息

J Mol Model. 2023 Nov 11;29(12):366. doi: 10.1007/s00894-023-05767-2.

Abstract

CONTEXT

Since the outbreak of COVID-19 in December 2019, it developed into a pandemic affecting all the countries and millions of people around the globe. Until now, there is no medicine available to contain the spread of the virus. As an aid to drug discovery, the molecular docking and molecular dynamic tools were applied extensively. In silico studies made it possible for rapid screening of potential molecules as possible inhibitors/drugs against the targeted proteins. As a continuation of our drug discovery research, we have carried out molecular docking studies of our 12 reported unnatural nucleosides and 14 designer Avigan analogs with SARS-CoV-2, RNA-dependent RNA polymerase (RdRp), which we want to report herein. The same calculation was also carried out, taking 11 known/under trail/commercial nucleoside drug molecules for a comparison of the binding interactions in the catalytic site of RdRp. The docking results and binding efficiencies of our reported nucleosides and designer nucleosidic were compared with the binding energy of commercially available drugs such as remdesevir and favipiravir. Furthermore, we evaluated the protein-drug binding efficiency and stability of the best docked molecules by molecular dynamic studies (MD). From our study, we have found that few of our proposed drugs show promising binding efficiency at the catalytic pocket of SARS-CoV-2 RdRp and can be a promising RdRp inhibitor drug candidate. Hence, this study will be of importance to make progress toward developing successful nucleoside-based drugs and conduct the antiviral test in the wet lab to understand their efficacy against COVID-19.

METHOD

All the docking studies were carried out with AutoDock 4.2, AutoDock Vina and Molegro Virtual Docker. Following the docking studies, the MD simulations were carried out following the standard protocol with the GROMACS ver. 2019.6. by applying the CHARMM36 all-atom biomolecular force field. The drug-protein interaction was studied using the Biovia Discovery Studio suite, Ligplot software, and Protein-Ligand Interaction Profiler (PLIP).

摘要

背景

自2019年12月新型冠状病毒肺炎疫情爆发以来,它已发展成为一场影响全球所有国家和数百万人的大流行病。到目前为止,尚无药物可抑制该病毒的传播。作为药物发现的辅助手段,分子对接和分子动力学工具得到了广泛应用。计算机模拟研究使得快速筛选作为针对目标蛋白的潜在抑制剂/药物的潜在分子成为可能。作为我们药物发现研究的延续,我们对12种已报道的非天然核苷和14种设计的阿比多尔类似物与严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的RNA依赖性RNA聚合酶(RdRp)进行了分子对接研究,我们想在此报告。我们还进行了同样的计算,以11种已知/正在试验/市售的核苷药物分子为对照,比较它们在RdRp催化位点的结合相互作用。将我们报道的核苷和设计核苷的对接结果及结合效率与瑞德西韦和法匹拉韦等市售药物的结合能进行了比较。此外,我们通过分子动力学研究(MD)评估了最佳对接分子的蛋白质-药物结合效率和稳定性。从我们的研究中发现,我们提出的几种药物在SARS-CoV-2 RdRp的催化口袋处显示出有前景的结合效率,可能成为有前景的RdRp抑制剂药物候选物。因此,本研究对于开发成功的核苷类药物取得进展以及在湿实验室进行抗病毒试验以了解它们对新型冠状病毒肺炎的疗效具有重要意义。

方法

所有对接研究均使用AutoDock 4.2、AutoDock Vina和Molegro Virtual Docker进行。对接研究之后,按照标准方案使用GROMACS ver. 2019.6进行MD模拟,应用CHARMM36全原子生物分子力场。使用Biovia Discovery Studio套件、Ligplot软件和蛋白质-配体相互作用分析器(PLIP)研究药物-蛋白质相互作用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验