Discovery of a Potential Allosteric Site in the SARS-CoV-2 Spike Protein and Targeting Allosteric Inhibitor to Stabilize the RBD Down State using a Computational Approach.

IF 1.5 4区医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2024-01-01 DOI:10.2174/1573409919666230726142418

Tong Li, Zheng Yan, Wei Zhou, Qun Liu, Jinfeng Liu, Haibing Hua

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Abstract

Background: The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a worldwide public health crisis. At present, the development of effective drugs and/or related therapeutics is still the most urgent and important task for combating the virus. The viral entry and associated infectivity mainly rely on its envelope spike protein to recognize and bind to the host cell receptor angiotensin-converting enzyme 2 (ACE2) through a conformational switch of the spike receptor binding domain (RBD) from inactive to active state. Thus, it is of great significance to design an allosteric inhibitor targeting spike to lock it in the inactive and ACE2-inaccessible state.

Objective: This study aims to discover the potential broad-spectrum allosteric inhibitors capable of binding and stabilizing the diverse spike variants, including the wild type, Delta, and Omicron, in the inactive RBD down state.

Methods: In this work, we first detected a potential allosteric pocket within the SARS-CoV-2 spike protein. Then, we performed large-scale structure-based virtual screening by targeting the putative allosteric pocket to identify allosteric inhibitors that could stabilize the spike inactive state. Molecular dynamics simulations were further carried out to evaluate the effects of compound binding on the stability of spike RBD.

Results: Finally, we identified three potential allosteric inhibitors, CPD3, CPD5, and CPD6, against diverse SARS-CoV-2 variants, including Wild-type, Delta, and Omicron variants. Our simulation results showed that the three compounds could stably bind the predicted allosteric site and effectively stabilize the spike in the inactive state.

Conclusion: The three compounds provide novel chemical structures for rational drug design targeting spike protein, which is expected to greatly assist in the development of new drugs against SARS-CoV-2.

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利用计算方法发现 SARS-CoV-2 Spike 蛋白中的潜在异构位点并锁定异构抑制剂以稳定 RBD 下降状态。

背景：由严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2）引起的新型冠状病毒病 2019（COVID-19）已导致全球公共卫生危机。目前，开发有效药物和/或相关疗法仍是抗击该病毒最紧迫和最重要的任务。病毒的进入和相关感染性主要依赖于其包膜尖峰蛋白通过尖峰受体结合域（RBD）从非活性状态到活性状态的构象转换，识别宿主细胞受体血管紧张素转换酶 2（ACE2）并与之结合。因此，设计一种针对穗状受体的异构抑制剂，将其锁定在非活性和 ACE2 不能进入的状态具有重要意义：本研究旨在发现潜在的广谱异构抑制剂，这些抑制剂能够与野生型、Delta 和 Omicron 等不同的 spike 变体结合并将其稳定在非活性 RBD 下降状态：在这项工作中，我们首先在 SARS-CoV-2 穗状病毒蛋白中发现了一个潜在的异构口袋。然后，我们针对这个潜在的异构口袋进行了大规模的基于结构的虚拟筛选，以确定能稳定尖峰非活性状态的异构抑制剂。我们还进一步进行了分子动力学模拟，以评估化合物结合对尖峰 RBD 稳定性的影响：最后，我们确定了 CPD3、CPD5 和 CPD6 这三种潜在的异位抑制剂，它们针对的是不同的 SARS-CoV-2 变异株，包括野生型、Delta 和 Omicron 变异株。我们的模拟结果表明，这三种化合物能与预测的异构位点稳定结合，并有效地将尖峰稳定在非活性状态：结论：这三种化合物为针对尖峰蛋白的合理药物设计提供了新的化学结构，有望极大地促进抗 SARS-CoV-2 新药的开发。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Current computer-aided drug design 医学-计算机：跨学科应用

CiteScore

3.70

自引率

5.90%

发文量

审稿时长

>12 weeks

期刊介绍： Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.