Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts 01605, USA.
Protein Sci. 2011 Sep;20(9):1576-86. doi: 10.1002/pro.687. Epub 2011 Aug 8.
Most scoring functions for protein-protein docking algorithms are either atom-based or residue-based, with the former being able to produce higher quality structures and latter more tolerant to conformational changes upon binding. Earlier, we developed the ZRANK algorithm for reranking docking predictions, with a scoring function that contained only atom-based terms. Here we combine ZRANK's atom-based potentials with five residue-based potentials published by other labs, as well as an atom-based potential IFACE that we published after ZRANK. We simultaneously optimized the weights for selected combinations of terms in the scoring function, using decoys generated with the protein-protein docking algorithm ZDOCK. We performed rigorous cross validation of the combinations using 96 test cases from a docking benchmark. Judged by the integrative success rate of making 1000 predictions per complex, addition of IFACE and the best residue-based pair potential reduced the number of cases without a correct prediction by 38 and 27% relative to ZDOCK and ZRANK, respectively. Thus combination of residue-based and atom-based potentials into a scoring function can improve performance for protein-protein docking. The resulting scoring function is called IRAD (integration of residue- and atom-based potentials for docking) and is available at http://zlab.umassmed.edu.
大多数蛋白质-蛋白质对接算法的评分函数要么基于原子,要么基于残基,前者能够产生更高质量的结构,而后者在结合时对构象变化更具容忍性。早些时候,我们开发了 ZRANK 算法来重新排序对接预测,其评分函数仅包含基于原子的项。在这里,我们将 ZRANK 的基于原子的势能与其他实验室发表的五个基于残基的势能以及我们在 ZRANK 之后发表的基于原子的 IFACE 相结合。我们使用蛋白质-蛋白质对接算法 ZDOCK 生成的诱饵同时优化了评分函数中选定术语组合的权重。我们使用来自对接基准测试的 96 个测试用例对组合进行了严格的交叉验证。通过对每个复合物进行 1000 次预测的综合成功率进行判断,与 ZDOCK 和 ZRANK 相比,添加 IFACE 和最佳基于残基的对势能分别使没有正确预测的案例数量减少了 38%和 27%。因此,将基于残基和基于原子的势能组合成一个评分函数可以提高蛋白质-蛋白质对接的性能。所得评分函数称为 IRAD(用于对接的基于残基和基于原子的势能的整合),可在 http://zlab.umassmed.edu 获得。