DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins.
DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins.
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DOI：
10.1016/j.compbiomed.2021.104943
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发表时间：
2021-12
影响因子：
7.7
通讯作者：
Zanatta G
中科院分区：
文献类型：
--
作者：
Hall-Swan S;Devaurs D;Rigo MM;Antunes DA;Kavraki LE;Zanatta G
为了应对持续的 COVID-19 大流行，我们开展了前所未有的研究工作。这包括确定数百种 SARS-CoV-2 蛋白的晶体结构，以及众多虚拟筛选项目，在大型化合物库中搜索潜在的药物抑制剂。不幸的是，这些举措在生产有效的 SARS-CoV-2 蛋白抑制剂方面取得的成功非常有限。一个原因可能是这些计算工作中经常被忽视的因素：受体灵活性。为了解决这个问题，我们实施了一种计算工具，用于与 SARS-CoV-2 蛋白进行整体对接。我们从蛋白质数据库和计算机分子动力学模拟中提取了具有代表性的蛋白质构象集合。 12 个预先计算的 SARS-CoV-2 蛋白质构象集合现已可通过名为 DINC-COVID (dinc-covid.kavrakilab.org) 的用户友好型网络服务器进行集合对接。我们使用两种 SARS-CoV-2 蛋白的测试抑制剂数据验证了 DINC-COVID，获得了对接衍生的结合能与实验确定的结合亲和力之间的良好相关性。一些最好的结果是在通过室温晶体学解析的大配体数据集上获得的，因此捕获了替代的受体构象。此外，我们还表明，DINC-COVID 中可用的整体捕获了不同范围的受体灵活性，并且这种多样性有助于寻找配体的替代结合模式。总的来说，我们的工作强调了对接研究中受体灵活性的重要性，并为识别 SARS-CoV-2 蛋白的新抑制剂提供了一个平台。
An unprecedented research effort has been undertaken in response to the ongoing COVID-19 pandemic. This has included the determination of hundreds of crystallographic structures of SARS-CoV-2 proteins, and numerous virtual screening projects searching large compound libraries for potential drug inhibitors. Unfortunately, these initiatives have had very limited success in producing effective inhibitors against SARS-CoV-2 proteins. A reason might be an often overlooked factor in these computational efforts: receptor flexibility. To address this issue we have implemented a computational tool for ensemble docking with SARS-CoV-2 proteins. We have extracted representative ensembles of protein conformations from the Protein Data Bank and from in silico molecular dynamics simulations. Twelve pre-computed ensembles of SARS-CoV-2 protein conformations have now been made available for ensemble docking via a user-friendly webserver called DINC-COVID (dinc-covid.kavrakilab.org). We have validated DINC-COVID using data on tested inhibitors of two SARS-CoV-2 proteins, obtaining good correlations between docking-derived binding energies and experimentally-determined binding affinities. Some of the best results have been obtained on a dataset of large ligands resolved via room temperature crystallography, and therefore capturing alternative receptor conformations. In addition, we have shown that the ensembles available in DINC-COVID capture different ranges of receptor flexibility, and that this diversity is useful in finding alternative binding modes of ligands. Overall, our work highlights the importance of accounting for receptor flexibility in docking studies, and provides a platform for the identification of new inhibitors against SARS-CoV-2 proteins.
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