PROCOS: Computational Analysis of Protein-Protein Complexes
PROCOS: Computational Analysis of Protein-Protein Complexes
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DOI：
10.1002/jcc.21837
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发表时间：
2011-09-01
影响因子：
3
通讯作者：
Gronwald, Wolfram
中科院分区：
文献类型：
--
作者：
Fink, Florian;Hochrein, Jochen;Gronwald, Wolfram
蛋白质对接的主要挑战之一是对许多假定的解决方案进行有意义的评估。在这里，我们提出了一个程序（PROCOS），计算一个概率样的措施是本地一个给定的复杂。与通常用于分析复杂结构的分数相比，计算的概率提供了提供固定范围的期望值的优点。原则上，这将允许比较对应于用相同算法求解的不同目标的模型。判断的基础上分布的属性来自一个大型数据库的本地和假复合物。对于复杂的分析，PROCOS使用天然和假复合物的这些属性分布以及支持向量机（SVM）。将PROCOS与ZRANK和DFIRE的既定评分方案进行比较。采用一组实验解决的天然配合物，高概率值超过50%，获得了90%的这些结构。接下来，在Dockground诱饵集的40个二元目标、RosettaDock诱饵集的14个目标和参与卡普里评分评估的9个目标上测试了PROCOS的性能。同样，使用基于概率的评分系统的优点变得明显，并且在排名靠前的复合物中发现了合理数量的近天然复合物。总之，提出了一种新型的全自动化方法，可以可靠地评估蛋白质-蛋白质复合物。(C)2011 Wiley Periodicals，Inc. J Comput Chem 32：2575-2586，2011
One of the main challenges in protein protein docking is a meaningful evaluation of the many putative solutions. Here we present a program (PROCOS) that calculates a probability-like measure to be native for a given complex. In contrast to scores often used for analyzing complex structures, the calculated probabilities offer the advantage of providing a fixed range of expected values. This will allow, in principle, the comparison of models corresponding to different targets that were solved with the same algorithm. Judgments are based on distributions of properties derived from a large database of native and false complexes. For complex analysis PROCOS uses these property distributions of native and false complexes together with a support vector machine (SVM). PROCOS was compared to the established scoring schemes of ZRANK and DFIRE. Employing a set of experimentally solved native complexes, high probability values above 50% were obtained for 90% of these structures. Next, the performance of PROCOS was tested on the 40 binary targets of the Dockground decoy set, on 14 targets of the RosettaDock decoy set and on 9 targets that participated in the CAPRI scoring evaluation. Again the advantage of using a probability-based scoring system becomes apparent and a reasonable number of near native complexes was found within the top ranked complexes. In conclusion, a novel fully automated method is presented that allows the reliable evaluation of protein-protein complexes. (C) 2011 Wiley Periodicals, Inc. J Comput Chem 32: 2575-2586, 2011