发现天然来源的Mpro抑制剂作为COVID-19的候选治疗药物:基于结构的药效团筛选结合QSAR分析

IF 2.8 4区医学 Q3 CHEMISTRY, MEDICINAL

Molecular Informatics Pub Date : 2023-04-01 DOI:10.1002/minf.202200198

Mohammad A Khanfar, Nada Salaas, Reem Abumostafa

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引用次数: 1

摘要

主蛋白酶(Mpro)是SARS-CoV-2生命周期的必需酶，也是治疗COVID-19感染的有效靶点。采用基于结构的药效团模型结合QSAR计算，从天然产物库中鉴定Mpro抑制剂的新化学支架。根据相应的x射线晶体结构，人工建立了数百个药效团模型。通过受试者工作特征(ROC)曲线分析验证药效团模型，并使用统计最优的QSAR方程选择药效团模型，作为挖掘AnalytiCon Discovery天然产物数据库的3d搜索工具。捕获的显示最高预测抑制活性的命中进行生物测定。在低微摩尔范围内成功鉴定出三种活性Mpro抑制剂(假黄素A、乳苦苷和高松素)的IC50值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Discovery of natural-derived Mpro inhibitors as therapeutic candidates for COVID-19: Structure-based pharmacophore screening combined with QSAR analysis.

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Discovery of natural-derived M^pro inhibitors as therapeutic candidates for COVID-19: Structure-based pharmacophore screening combined with QSAR analysis.

The main protease (M^pro ) is an essential enzyme for the life cycle of SARS-CoV-2 and a validated target for treatment of COVID-19 infection. Structure-based pharmacophore modeling combined with QSAR calculations were employed to identify new chemical scaffolds of M^pro inhibitors from natural products repository. Hundreds of pharmacophore models were manually built from their corresponding X-ray crystallographic structures. A pharmacophore model that was validated by receiver operating characteristic (ROC) curve analysis and selected using the statistically optimum QSAR equation was implemented as a 3D-search tool to mine AnalytiCon Discovery database of natural products. Captured hits that showed the highest predicted inhibitory activities were bioassayed. Three active M^pro inhibitors (pseurotin A, lactupicrin, and alpinetin) were successfully identified with IC₅₀ values in low micromolar range.

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来源期刊

Molecular Informatics CHEMISTRY, MEDICINAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY

CiteScore

7.30

自引率

2.80%

发文量

审稿时长

3 months

期刊介绍： Molecular Informatics is a peer-reviewed, international forum for publication of high-quality, interdisciplinary research on all molecular aspects of bio/cheminformatics and computer-assisted molecular design. Molecular Informatics succeeded QSAR & Combinatorial Science in 2010. Molecular Informatics presents methodological innovations that will lead to a deeper understanding of ligand-receptor interactions, macromolecular complexes, molecular networks, design concepts and processes that demonstrate how ideas and design concepts lead to molecules with a desired structure or function, preferably including experimental validation. The journal''s scope includes but is not limited to the fields of drug discovery and chemical biology, protein and nucleic acid engineering and design, the design of nanomolecular structures, strategies for modeling of macromolecular assemblies, molecular networks and systems, pharmaco- and chemogenomics, computer-assisted screening strategies, as well as novel technologies for the de novo design of biologically active molecules. As a unique feature Molecular Informatics publishes so-called "Methods Corner" review-type articles which feature important technological concepts and advances within the scope of the journal.