SARS-CoV-2 主要蛋白酶潜在抑制剂的分层虚拟筛选:相似性搜索、药效学建模和分子对接研究

H. Mando, Iyad allous
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引用次数: 0

摘要

由严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起的 COVID-19 爆发导致了大范围的流行。各种方法涉及抗病毒疗法和其他药物的重新定位。包括口服抗病毒治疗在内的几种疗法代表了适应 COVID-19 大流行长期存在的一些方法。硅学研究为整个药物发现和开发过程提供了宝贵的见解,以配合全球克服这一流行病的努力。主要蛋白酶是病毒循环中的一个重要靶点。计算机辅助药物设计加速了潜在治疗方法的鉴定,包括口服治疗。这项工作旨在利用不同方面的硅学方法鉴定潜在的 SARS-CoV-2 主要蛋白酶抑制剂。通过相似性搜索筛选出与抑制剂PF-07321332相似的分子。同时,除了基于配体的药代动力学外,还得出了基于结构的药代动力学。在进行分子对接之前,药物相似性过滤器过滤了从相似性搜索和药效学建模中检索到的化合物。根据结合亲和力和 ADME 分析,4 个分子(CHEMBL218022、PubChem163362029、PubChem166149100 和 PubChem 162396459)被优先列为有望命中的化合物。上述化合物以前没有报道过,也没有实验研究和生物活性测定。我们这种省时的方法是发现新型 SARS-CoV-2 主要蛋白酶抑制剂的一种策略。我们的省时方法代表了发现新型 SARS-CoV-2 主要蛋白酶抑制剂的策略,最终的命中化合物可能被提名为发现新型 SARS-CoV-2 主要蛋白酶抑制剂的先导化合物。
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Hierarchical Virtual Screening of SARS-CoV-2 Main Protease Potential Inhibitors: Similarity Search, Pharmacophore Modeling, and Molecular Docking Study
The outbreak of COVID-19 caused by severe acute respiratory syndrome coronavirus2 (SARS-CoV-2) resulted in a widespread pandemic. Various approaches involved the repositioning of antiviral remedies and other medications. Several therapies, including oral antiviral treatments, represent some approaches to adapting to the long existence of the COVID-19 pandemic. In silico studies provide valuable insights throughout drug discovery and development in compliance with global efforts to overcome the pandemic. The main protease is an essential target in the viral cycle. Computer-aided drug design accelerates the identification of potential treatments, including oral therapy. This work aims to identify potential SARS-CoV-2 main protease inhibitors using different aspects of in silico approaches. In this work, we conducted a hierarchical virtual screening of SARS-CoV-2 main protease inhibitors. A similarity search was conducted to screen molecules similar to the inhibitor PF-07321332. Concurrently, structure-based pharmacophores, besides ligand-based pharmacophores, were derived. A drug-likeness filter filtered the compounds retrieved from similarity search and pharmacophore modeling before being subjected to molecular docking. The candidate molecules that showed higher affinity to the main protease than the reference inhibitor were further filtered by absorption, distribution, metabolism, and excretion (ADME) parameters. According to binding affinity and ADME analysis, four molecules (CHEMBL218022, PubChem163362029, PubChem166149100, and PubChem 162396459) were prioritized as promising hits. The compounds above were not reported before; no previous experimental studies and bioactive assays are available. Our time-saving approach represents a strategy for discovering novel SARS-CoV- 2 main protease inhibitors. The ultimate hits may be nominated as leads in discovering novel SARS-CoV-2 main protease inhibitors.
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来源期刊
Anti-Infective Agents
Anti-Infective Agents Pharmacology, Toxicology and Pharmaceutics-Pharmacology
CiteScore
1.50
自引率
0.00%
发文量
47
期刊介绍: Anti-Infective Agents publishes original research articles, full-length/mini reviews, drug clinical trial studies and guest edited issues on all the latest and outstanding developments on the medicinal chemistry, biology, pharmacology and use of anti-infective and anti-parasitic agents. The scope of the journal covers all pre-clinical and clinical research on antimicrobials, antibacterials, antiviral, antifungal, and antiparasitic agents. Anti-Infective Agents is an essential journal for all infectious disease researchers in industry, academia and the health services.
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