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Fragment dissolved molecular dynamics: a systematic and efficient method to locate binding sites
Physical Chemistry Chemical Physics ( IF 3.3 ) Pub Date : 2020-12-28 , DOI: 10.1039/d0cp05471b
Cristian Privat 1, 2, 3, 4 , José M. Granadino-Roldán 4, 5, 6, 7 , Jordi Bonet 1, 2, 3, 4 , Maria Santos Tomas 3, 4, 8, 9 , Juan J. Perez 3, 4, 9, 10 , Jaime Rubio-Martinez 1, 2, 3, 4
Affiliation  

Diverse computational methods to support fragment-based drug discovery (FBDD) are available in the literature. Despite their demonstrated efficacy in supporting FBDD campaigns, they exhibit some drawbacks such as protein denaturation or ligand aggregation that have not yet been clearly overcome in the framework of biomolecular simulations. In the present work, we discuss a systematic semi-automatic novel computational procedure, designed to surpass these difficulties. The method, named fragment dissolved Molecular Dynamics (fdMD), utilizes simulation boxes of solvated small fragments, adding a repulsive Lennard-Jones potential term to avoid aggregation, which can be easily used to solvate the targets of interest. This method has the advantage of solvating the target with a low number of ligands, thus preventing the denaturation of the target, while simultaneously generating a database of ligand-solvated boxes that can be used in further studies. A number of scripts are made available to analyze the results and obtain the descriptors proposed as a means to trustfully discard spurious binding sites. To test our method, four test cases of different complexity have been solvated with ligand boxes and four molecular dynamics runs of 200 ns length have been run for each system, which have been extended up to 1 μs when needed. The reported results point out that the selected number of replicas are enough to identify the correct binding sites irrespective of the initial structure, even in the case of proteins having several close binding sites for the same ligand. We also propose a set of descriptors to analyze the results, among which the average MMGBSA and the average KDEEP energies have emerged as the most robust ones.

中文翻译:

片段溶解的分子动力学:定位结合位点的系统有效方法

文献中提供了多种支持基于片段的药物发现(FBDD)的计算方法。尽管它们在支持FBDD运动方面具有证明的功效,但它们仍存在一些缺点,例如蛋白质变性或配体聚集,这些缺点在生物分子模拟的框架中尚未明显克服。在目前的工作中,我们讨论了系统的半自动新颖的计算程序,旨在克服这些困难。该方法名为片段溶解分子动力学(fdMD),它利用溶剂化小片段的模拟盒,添加了排斥性Lennard-Jones势能术语以避免聚集,可以轻松地将其用于溶解目标分子。该方法的优势是可以用较少数量的配体溶解目标,从而防止目标变性,同时生成可用于进一步研究的配体溶解盒数据库。提供了许多脚本来分析结果并获得提议的描述符,以作为可信任地丢弃虚假绑定位点的手段。为了测试我们的方法,已使用配体盒溶解了四个不同复杂度的测试用例,并对每个系统进行了四个200 ns长度的分子动力学实验,并在需要时将其扩展至1μs。报道的结果指出,即使在蛋白质具有相同配体的几个紧密结合位点的情况下,所选择的数目的复制子也足以识别正确的结合位点,而与初始结构无关。我们还提出了一组描述符来分析结果,其中平均值MMGBSA和平均值K DEEP能量已成为最强大的能量。
更新日期:2021-01-25
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