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通过解旋酶抑制剂再利用靶向 SARS-CoV-2 非结构蛋白 13,并通过基于药效团的筛选靶向非结构蛋白 16。

Targeting SARS-CoV-2 non-structural protein 13 via helicase-inhibitor-repurposing and non-structural protein 16 through pharmacophore-based screening.

机构信息

Department of Pharmacy, Faculty of Pharmacy, University of Dhaka, Dhaka, 1000, Bangladesh.

Department of Clinical Pharmacy and Pharmacology, Faculty of Pharmacy, University of Dhaka, Dhaka, 1000, Bangladesh.

出版信息

Mol Divers. 2023 Jun;27(3):1067-1085. doi: 10.1007/s11030-022-10468-8. Epub 2022 Jun 12.

Abstract

Novel drug compound hunting was carried out for SARS-CoV-2 proteins with low mutation susceptibility. The probability of escape mutation and drug resistance is lower if conserved microbial proteins are targeted by therapeutic drugs. Mutation rate of all SARS-CoV-2 proteins were analyzed via multiple sequence alignment Non-Structural Protein 13 and Non-Structural Protein 16 were selected for the current study due to low mutation rate among viral strains and significant functionality. Cross-species mutation rate analysis for NSP13 and NSP16 showed these are well-conserved proteins among four coronaviral species. Viral helicase inhibitors, identified using literature-mining, were docked against NSP13. Pharmacophore-based screening of 11,375 natural compounds was conducted for NSP16. Stabilities of top compounds inside human body were confirmed via molecular dynamic simulation. ADME properties and LD values of the helicase inhibitors and Ambinter natural compounds were analyzed. Compounds against NSP13 showed binding affinities between -10 and -5.9 kcal/mol whereby ivermectin and scutellarein showed highest binding energies of -10 and -9.9 kcal/mol. Docking of 18 hit compounds against NSP16 yielded binding affinities between -8.9 and -4.1 kcal/mol. Hamamelitannin and deacyltunicamycin were the top compounds with binding affinities of -8.9 kcal/mol and -8.4 kcal/mol. The top compounds showed stable ligand-protein interactions in molecular dynamics simulation. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, high binding affinity and molecular interactions. Conversion of these compounds into drugs after in vitro experimentation can become better treatment options to elevate COVID management.

摘要

针对 SARS-CoV-2 蛋白进行了新型药物化合物的搜索,这些蛋白的突变易感性较低。如果治疗药物针对保守的微生物蛋白,那么逃逸突变和耐药性的概率就较低。通过多序列比对分析了所有 SARS-CoV-2 蛋白的突变率。由于病毒株之间的突变率较低且具有重要的功能,因此选择了非结构蛋白 13 和非结构蛋白 16 进行当前研究。对 NSP13 和 NSP16 的跨种突变率分析表明,这些蛋白在四种冠状病毒物种中是高度保守的。使用文献挖掘鉴定了病毒解旋酶抑制剂,并对 NSP13 进行了对接。对 NSP16 进行了基于药效团的 11375 种天然化合物的筛选。通过分子动力学模拟确认了人体内顶级化合物的稳定性。分析了解旋酶抑制剂和 Ambinter 天然化合物的 ADME 性质和 LD 值。针对 NSP13 的化合物显示出 -10 到 -5.9 kcal/mol 的结合亲和力,其中伊维菌素和水飞蓟素显示出最高的结合能 -10 和 -9.9 kcal/mol。对 NSP16 的 18 种命中化合物的对接产生了 -8.9 到 -4.1 kcal/mol 的结合亲和力。Hamamelitannin 和去酰基衣霉素是具有 -8.9 kcal/mol 和 -8.4 kcal/mol 结合亲和力的顶级化合物。顶级化合物在分子动力学模拟中表现出稳定的配体-蛋白相互作用。分析表明,针对每个靶标蛋白的两种命中化合物都表现出稳定的行为、高结合亲和力和分子相互作用。将这些化合物转化为药物进行体外实验后,可能成为改善 COVID 管理的更好治疗选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/229a/9188638/aad3c1ae50e4/11030_2022_10468_Fig1_HTML.jpg

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