Strengths and weaknesses of data-driven docking in critical assessment of prediction of interactions
Strengths and weaknesses of data-driven docking in critical assessment of prediction of interactions
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DOI：
10.1002/prot.22814
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发表时间：
2010-11-15
影响因子：
2.9
通讯作者：
Bonvin, Alexandre M. J. J.
中科院分区：
文献类型：
--
作者：
de Vries, Sjoerd J.;Melquiond, Adrien S. J.;Bonvin, Alexandre M. J. J.
最近的 CAPRI 轮次引入了新的对接挑战，其形式包括蛋白质-RNA 复合物、多种替代接口以及需要同源建模的前所未有数量的靶标。我们在这里展示HADDOCK及其Web服务器在CAPRI实验中的性能，并讨论数据驱动对接的优点和缺点。 HADDOCK 成功检测了 9 个复合体中的 6 个（11 个目标中的 6 个），并准确预测了另外两个复合体的各个界面。 HADDOCK 服务器是第一个允许通用多体综合体同时对接的服务器，在其参与的 7 个综合体中，有 4 个取得了成功。在评分实验中，我们预测了任何组中目标数量最多的。 CAPRI 最后的结果揭示了数据驱动对接的主要弱点是它容易受到与界面或复合体化学计量相关的错误实验数据的影响。同时，实验和/或预测信息的使用也是我们方法的优势，对于那些可以获得准确实验信息的目标而言（例如，T40 的 10 个三星级预测！）。即使模型显示错误方向，各个界面通常都能得到很好的预测，对所有目标的平均覆盖率为 60% +/- 26%。这使得数据驱动的对接在生物学背景下特别有价值，可以指导定向诱变等实验研究。蛋白质 2010; 78：3242-3249。 (C) 2010 Wiley-Liss, Inc.
The recent CAPRI rounds have introduced new docking challenges in the form of protein-RNA complexes, multiple alternative interfaces, and an unprecedented number of targets for which homology modeling was required. We present here the performance of HADDOCK and its web server in the CAPRI experiment and discuss the strengths and weaknesses of data-driven docking. HADDOCK was successful for 6 out of 9 complexes (6 out of 11 targets) and accurately predicted the individual interfaces for two more complexes. The HADDOCK server, which is the first allowing the simultaneous docking of generic multi-body complexes, was successful in 4 out of 7 complexes for which it participated. In the scoring experiment, we predicted the highest number of targets of any group. The main weakness of data-driven docking revealed from these last CAPRI results is its vulnerability for incorrect experimental data related to the interface or the stoichiometry of the complex. At the same time, the use of experimental and/or predicted information is also the strength of our approach as evidenced for those targets for which accurate experimental information was available (e.g., the 10 three-stars predictions for T40!). Even when the models show a wrong orientation, the individual interfaces are generally well predicted with an average coverage of 60% +/- 26% over all targets. This makes data-driven docking particularly valuable in a biological context to guide experimental studies like, for example, targeted mutagenesis. Proteins 2010; 78:3242-3249. (C) 2010 Wiley-Liss, Inc.