A collaborative filtering approach for protein-protein docking scoring functions.
A collaborative filtering approach for protein-protein docking scoring functions.
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DOI：
10.1371/journal.pone.0018541
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发表时间：
2011-04-22
期刊：
影响因子：
3.7
通讯作者：
Poupon A
中科院分区：
文献类型：
--
作者：
Bourquard T;Bernauer J;Azé J;Poupon A
蛋白质-蛋白质对接过程传统上包括两个连续的任务：搜索算法生成大量模仿两种蛋白质之间存在的复合体的候选构象，并用评分函数对它们进行排序，以提取与天然相似的构象。我们已经证明，使用Voronoi结构和一组精心选择的参数，可以设计和优化准确的评分函数。然而，为了能够对交互组进行大规模的计算机探索，必须在10个排名最高的解决方案中找到一个接近原生的解决方案。这还不能由任何现有的评分功能来保证。本文介绍了一种新的构象排序方法。我们之前开发了一组评分函数，其中使用遗传算法进行学习。这些函数被用来给每个可能的构象分配一个等级。我们现在在协同过滤方案中使用不同的分类器（决策树、规则和支持向量机）得到了一个精炼的排名。新获得的评分函数使用10倍交叉验证进行评估，并与单独使用遗传算法或协同过滤获得的函数进行比较。该方法已成功应用于CAPRI评分系统。我们表明，对于12个目标中的10个，我们能够在10个排名最佳的解决方案中找到接近原生的构象。其中6个选择的近原生构象精度较高。最后，我们证明了该函数极大地丰富了近原生结构中100个最佳排列构象。
A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.
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DOI：
10.1002/prot.10390
发表时间：
2003-07-01
期刊：
PROTEINS-STRUCTURE FUNCTION AND GENETICS
影响因子：
--
作者：
Chen, R;Mintseris, J;Weng, ZP
通讯作者：
Weng, ZP
影响因子：
2.9
作者：
Andrusier, Nelly;Mashiach, Efrat;Nussinov, Ruth;Wolfson, Haim J.
通讯作者：
Wolfson, Haim J.
DOI：
10.1016/s0925-7721(01)00054-2
发表时间：
2002-05-01
影响因子：
0.6
作者：
Boissonnat, JD;Devillers, O;Yvinec, M
通讯作者：
Yvinec, M
影响因子：
2.9
作者：
Lensink, Marc F.;Mendez, Raul;Wodak, Shoshana J.
通讯作者：
Wodak, Shoshana J.
影响因子：
4.4
作者：
Kastritis, Panagiotis L.;Bonvin, Alexandre M. J. J.
通讯作者：
Bonvin, Alexandre M. J. J.