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通过基于残基能量分解的药效团建模、分子对接和分子动力学模拟鉴定 SARS-CoV-2 的 RNA 依赖性 RNA 聚合酶的非核苷抑制剂。

Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation.

机构信息

Institute of Biotechnology and Genetic Engineering, The University of Agriculture, Peshawar 25000, Pakistan.

Department of Biotechnology and Genetic Engineering, Hazara University Mansehra, 2100, Pakistan; Natural and Medical Sciences Research Center, University of Nizwa, Birkat-ul-Mouz 616, Nizwa, Sultanate of Oman.

出版信息

J Infect Public Health. 2023 Apr;16(4):501-519. doi: 10.1016/j.jiph.2023.02.009. Epub 2023 Feb 14.

Abstract

BACKGROUND AND OBJECTIVE

The current coronavirus disease-2019 (COVID-19) pandemic has triggered a worldwide health and economic crisis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes the disease and completes its life cycle using the RNA-dependent RNA-polymerase (RdRp) enzyme, a prominent target for antivirals. In this study, we have computationally screened ∼690 million compounds from the ZINC20 database and 11,698 small molecule inhibitors from DrugBank to find existing and novel non-nucleoside inhibitors for SARS-CoV-2 RdRp.

METHODS

Herein, a combination of the structure-based pharmacophore modeling and hybrid virtual screening methods, including per-residue energy decomposition-based pharmacophore screening, molecular docking, pharmacokinetics, and toxicity evaluation were employed to retrieve novel as well as existing RdRp non-nucleoside inhibitors from large chemical databases. Besides, molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method were used to investigate the binding stability and calculate the binding free energy of RdRp-inhibitor complexes.

RESULTS

Based on docking scores and significant binding interactions with crucial residues (Lys553, Arg557, Lys623, Cys815, and Ser816) in the RNA binding site of RdRp, three existing drugs, ZINC285540154, ZINC98208626, ZINC28467879, and five compounds from ZINC20 (ZINC739681614, ZINC1166211307, ZINC611516532, ZINC1602963057, and ZINC1398350200) were selected, and the conformational stability of RdRp due to their binding was confirmed through molecular dynamics simulation. The free energy calculations revealed these compounds possess strong binding affinities for RdRp. In addition, these novel inhibitors exhibited drug-like features, good absorption, distribution, metabolism, and excretion profile and were found to be non-toxic.

CONCLUSION

The compounds identified in the study by multifold computational strategy can be validated in vitro as potential non-nucleoside inhibitors of SARS-CoV-2 RdRp and holds promise for the discovery of novel drugs against COVID-19 in future.

摘要

背景与目的

当前的 2019 年冠状病毒病(COVID-19)大流行引发了全球卫生和经济危机。严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起该疾病,并使用 RNA 依赖性 RNA 聚合酶(RdRp)酶完成其生命周期,该酶是抗病毒药物的主要靶标。在这项研究中,我们通过计算从 ZINC20 数据库中筛选了约 6.9 亿种化合物和来自 DrugBank 的 11698 种小分子抑制剂,以寻找针对 SARS-CoV-2 RdRp 的现有和新型非核苷抑制剂。

方法

在此,我们采用了基于结构的药效团建模和混合虚拟筛选方法的组合,包括基于残基的能量分解药效团筛选、分子对接、药代动力学和毒性评估,从大型化学数据库中检索新型和现有的 RdRp 非核苷抑制剂。此外,还使用分子动力学模拟和分子力学/广义 Born 表面积(MM/GBSA)方法研究了 RdRp-抑制剂复合物的结合稳定性并计算了结合自由能。

结果

基于对接评分以及与 RdRp 的 RNA 结合部位中的关键残基(Lys553、Arg557、Lys623、Cys815 和 Ser816)的显著结合相互作用,从 DrugBank 中选择了三种现有药物(ZINC285540154、ZINC98208626 和 ZINC28467879)和 ZINC20 中的五种化合物(ZINC739681614、ZINC1166211307、ZINC611516532、ZINC1602963057 和 ZINC1398350200),并通过分子动力学模拟证实了 RdRp 由于结合而具有构象稳定性。自由能计算表明,这些化合物对 RdRp 具有很强的结合亲和力。此外,这些新型抑制剂表现出类药物特征,具有良好的吸收、分布、代谢和排泄特征,并且被发现无毒。

结论

通过多步计算策略鉴定的化合物可在体外作为 SARS-CoV-2 RdRp 的潜在非核苷抑制剂进行验证,并有望在未来发现针对 COVID-19 的新型药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e28/9927802/cc613d2378d9/gr1_lrg.jpg

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