Vajda Sandor, Yueh Christine, Beglov Dmitri, Bohnuud Tanggis, Mottarella Scott E, Xia Bing, Hall David R, Kozakov Dima
Department of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
Department of Chemistry, Boston University, Boston, Massachusetts, 02215.
Proteins. 2017 Mar;85(3):435-444. doi: 10.1002/prot.25219. Epub 2017 Jan 5.
The heavily used protein-protein docking server ClusPro performs three computational steps as follows: (1) rigid body docking, (2) RMSD based clustering of the 1000 lowest energy structures, and (3) the removal of steric clashes by energy minimization. In response to challenges encountered in recent CAPRI targets, we added three new options to ClusPro. These are (1) accounting for small angle X-ray scattering data in docking; (2) considering pairwise interaction data as restraints; and (3) enabling discrimination between biological and crystallographic dimers. In addition, we have developed an extremely fast docking algorithm based on 5D rotational manifold FFT, and an algorithm for docking flexible peptides that include known sequence motifs. We feel that these developments will further improve the utility of ClusPro. However, CAPRI emphasized several shortcomings of the current server, including the problem of selecting the right energy parameters among the five options provided, and the problem of selecting the best models among the 10 generated for each parameter set. In addition, results convinced us that further development is needed for docking homology models. Finally, we discuss the difficulties we have encountered when attempting to develop a refinement algorithm that would be computationally efficient enough for inclusion in a heavily used server. Proteins 2017; 85:435-444. © 2016 Wiley Periodicals, Inc.
频繁使用的蛋白质-蛋白质对接服务器ClusPro执行以下三个计算步骤:(1)刚体对接;(2)基于均方根偏差(RMSD)对1000个最低能量结构进行聚类;(3)通过能量最小化消除空间冲突。针对近期CAPRI靶标中遇到的挑战,我们为ClusPro添加了三个新选项。这些选项包括:(1)对接时考虑小角X射线散射数据;(2)将成对相互作用数据视为约束条件;(3)区分生物学二聚体和晶体学二聚体。此外,我们开发了一种基于5D旋转流形快速傅里叶变换(FFT)的极快速对接算法,以及一种用于对接包含已知序列基序的柔性肽的算法。我们认为这些进展将进一步提高ClusPro的实用性。然而,CAPRI强调了当前服务器的几个缺点,包括在提供的五个选项中选择正确能量参数的问题,以及在为每个参数集生成的10个模型中选择最佳模型的问题。此外,结果让我们确信对接同源模型还需要进一步发展。最后,我们讨论了在尝试开发一种计算效率足够高、可纳入频繁使用的服务器的优化算法时遇到的困难。《蛋白质》2017年;85卷:435 - 444页。© 2016威利期刊公司