利用 AlphaFold2-RAVE 增强 AlphaFold2 在蛋白质构象选择性药物发现方面的能力

IF 6.4 1区 生物学 Q1 BIOLOGY
Xinyu Gu, Akashnathan Aranganathan, Pratyush Tiwary
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引用次数: 0

摘要

小分子药物设计取决于配体与蛋白质的共晶体结构。尽管 AlphaFold2 在蛋白质原生结构预测方面取得了长足进步,但它只关注配体结构,而忽略了相关的整体结构。此外,选择性药物的设计往往得益于针对不同的可变构象。因此,AlphaFold2 模型在虚拟筛选和药物发现中的直接应用仍处于试验阶段。在这里,我们展示了一个基于 AlphaFold2 的框架,该框架与全原子增强采样分子动力学和诱导拟合对接相结合,被命名为 AF2RAVE-Glide,用于进行基于计算模型的小分子与蛋白激酶构象的结合。我们在三种不同的哺乳动物蛋白激酶及其 I 型和 II 型抑制剂上演示了 AF2RAVE-Glide 工作流程,特别强调了已知 II 型激酶抑制剂的结合,这些抑制剂针对的是可转移的经典 DFG-out 状态。这些状态不易从 AlphaFold2 中采样。在这里,我们展示了如何利用 AF2RAVE 以足够高的精度对不同激酶的这些可转移构象进行采样,从而使已知 II 型激酶抑制剂的后续对接计算成功率超过 50%。我们相信该方案可用于其他激酶和更多蛋白质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE
Small-molecule drug design hinges on obtaining co-crystallized ligand-protein structures. Despite AlphaFold2’s strides in protein native structure prediction, its focus on apo structures overlooks ligands and associated holo structures. Moreover, designing selective drugs often benefits from the targeting of diverse metastable conformations. Therefore, direct application of AlphaFold2 models in virtual screening and drug discovery remains tentative. Here, we demonstrate an AlphaFold2-based framework combined with all-atom enhanced sampling molecular dynamics and Induced Fit docking, named AF2RAVE-Glide, to conduct computational model-based small-molecule binding of metastable protein kinase conformations, initiated from protein sequences. We demonstrate the AF2RAVE-Glide workflow on three different mammalian protein kinases and their type I and II inhibitors, with special emphasis on binding of known type II kinase inhibitors which target the metastable classical DFG-out state. These states are not easy to sample from AlphaFold2. Here, we demonstrate how with AF2RAVE these metastable conformations can be sampled for different kinases with high enough accuracy to enable subsequent docking of known type II kinase inhibitors with more than 50% success rates across docking calculations. We believe the protocol should be deployable for other kinases and more proteins generally.
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来源期刊
eLife
eLife BIOLOGY-
CiteScore
12.90
自引率
3.90%
发文量
3122
审稿时长
17 weeks
期刊介绍: eLife is a distinguished, not-for-profit, peer-reviewed open access scientific journal that specializes in the fields of biomedical and life sciences. eLife is known for its selective publication process, which includes a variety of article types such as: Research Articles: Detailed reports of original research findings. Short Reports: Concise presentations of significant findings that do not warrant a full-length research article. Tools and Resources: Descriptions of new tools, technologies, or resources that facilitate scientific research. Research Advances: Brief reports on significant scientific advancements that have immediate implications for the field. Scientific Correspondence: Short communications that comment on or provide additional information related to published articles. Review Articles: Comprehensive overviews of a specific topic or field within the life sciences.
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