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值得关注的体重问题:基于加权集成方法的口袋亚结构探索器(SubPEx),用于增强结合口袋构象采样。

Worth the Weight: Sub-Pocket EXplorer (SubPEx), a Weighted Ensemble Method to Enhance Binding-Pocket Conformational Sampling.

机构信息

Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States.

出版信息

J Chem Theory Comput. 2023 Sep 12;19(17):5677-5689. doi: 10.1021/acs.jctc.3c00478. Epub 2023 Aug 16.

Abstract

Structure-based virtual screening (VS) is an effective method for identifying potential small-molecule ligands, but traditional VS approaches consider only a single binding-pocket conformation. Consequently, they struggle to identify ligands that bind to alternate conformations. Ensemble docking helps address this issue by incorporating multiple conformations into the docking process, but it depends on methods that can thoroughly explore pocket flexibility. We here introduce Sub-Pocket EXplorer (SubPEx), an approach that uses weighted ensemble (WE) path sampling to accelerate binding-pocket sampling. As proof of principle, we apply SubPEx to three proteins relevant to drug discovery: heat shock protein 90, influenza neuraminidase, and yeast hexokinase 2. SubPEx is available free of charge without registration under the terms of the open-source MIT license: http://durrantlab.com/subpex/.

摘要

基于结构的虚拟筛选 (VS) 是一种识别潜在小分子配体的有效方法,但传统的 VS 方法仅考虑单个结合口袋构象。因此,它们难以识别与其他构象结合的配体。通过将多个构象纳入对接过程,集合对接有助于解决这个问题,但它依赖于能够彻底探索口袋灵活性的方法。我们在这里介绍 Sub-Pocket EXplorer (SubPEx),这是一种使用加权集合 (WE) 路径采样来加速结合口袋采样的方法。作为原理验证,我们将 SubPEx 应用于与药物发现相关的三种蛋白质:热休克蛋白 90、流感神经氨酸酶和酵母己糖激酶 2。SubPEx 可根据开放源代码 MIT 许可证的条款免费使用,无需注册:http://durrantlab.com/subpex/。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e350/10500992/1a14b768df66/ct3c00478_0002.jpg

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