iAlign: a method for the structural comparison of protein-protein interfaces
iAlign: a method for the structural comparison of protein-protein interfaces
复制标题
DOI：
10.1093/bioinformatics/btq404
复制
发表时间：
2010-09-01
期刊：
影响因子：
5.8
通讯作者：
Skolnick, Jeffrey
中科院分区：
文献类型：
--
作者：
Gao, Mu;Skolnick, Jeffrey
动机：蛋白质之间的相互作用在许多细胞过程中起着至关重要的作用。蛋白质-蛋白质复合结构的快速积累为蛋白质-蛋白质相互作用的比较研究提供了前所未有的机会。为了促进这类研究，有必要开发一种准确而高效的计算算法来比较蛋白质-蛋白质相互作用模式。虽然针对单个蛋白质的结构比对方法很多，但对蛋白质-蛋白质复合体的结构比对方法很少。结果：我们提出了一种新的蛋白质-蛋白质界面比对方法iAlign。提出了一种新的界面相似性评分方法，并实现了迭代动态规划算法。我们发现相似性得分服从极值分布。利用统计模型，我们对它们的统计意义进行了经验估计，这与人类专家的人工分类很好地吻合。IAlign在人工对接模型和实验结构上进行了大规模测试。在对1517个二聚体的基准测试中，iAlign成功地检测到了生物上相关的、结构相似的蛋白质-蛋白质界面，覆盖率为90%，每次查询的误差为0.05。与以前发布的方法相比，iAlign的准确性和效率要高得多。
Motivation: Protein-protein interactions play an essential role in many cellular processes. The rapid accumulation of protein-protein complex structures provides an unprecedented opportunity for comparative studies of protein-protein interactions. To facilitate such studies, it is necessary to develop an accurate and efficient computational algorithm for the comparison of protein-protein interaction modes. While there are many structural comparison approaches developed for individual proteins, very few methods are available for protein-protein complexes.Results: We present a novel interface alignment method, iAlign, for the structural alignment of protein-protein interfaces. New scoring schemes for measuring interface similarity are introduced, and an iterative dynamic programming algorithm is implemented. We find that the similarity scores follow extreme value distributions. Using statistical models, we empirically estimate their statistical significance, which is in good agreement with manual classifications by human experts. Large-scale tests of iAlign were conducted on both artificial docking models and experimental structures. In a benchmark test on 1517 dimers, iAlign successfully detects biologically related, structurally similar protein-protein interfaces at a coverage percentage of 90% and an error per query of 0.05. When compared against previously published methods, iAlign is substantially more accurate and efficient.