Are Scoring Functions in Protein-Protein Docking Ready To Predict Interactomes? Clues from a Novel Binding Affinity Benchmark
Are Scoring Functions in Protein-Protein Docking Ready To Predict Interactomes? Clues from a Novel Binding Affinity Benchmark
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DOI：
10.1021/pr9009854
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发表时间：
2010-05-01
影响因子：
4.4
通讯作者：
Bonvin, Alexandre M. J. J.
中科院分区：
文献类型：
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作者：
Kastritis, Panagiotis L.;Bonvin, Alexandre M. J. J.
设计一个理想的蛋白质-蛋白质对接的评分函数，同时预测复合物的结合亲和力是结构蛋白质组学的挑战之一。这样的评分功能将打开途径，以在计算机上，大规模的注释和预测完整的相互作用组。在这里，我们提出了一个蛋白质-蛋白质结合亲和力基准组成的81复合物的结合常数（Kd的）。该基准用于评估九种常用评分算法沿着自由能预测算法在预测结合亲和力的能力方面的性能。我们的结果揭示了一个穷人之间的相关性结合亲和力和分数的所有算法测试。然而，当结合亲和力数据根据其确定的方法进行分类时，突出了基准的多样性和有效性。通过将复合物进一步分类为低、中和高亲和力组，出现了显著的相关性，其中一些在将数据分成更多类后被保留，显示了这些相关性的稳健性。尽管如此，结合亲和力的准确预测仍然超出了我们的能力范围，因为每组内平均得分的相关标准偏差很大。所有上述观察结果表明，需要改进现有的评分函数或设计新的共识工具，以准确预测给定蛋白质-蛋白质复合物的结合亲和力。在这项工作中开发的基准将作为实现这一目标不可或缺的来源。
The design of an ideal scoring function for protein-protein docking that would also predict the binding affinity of a complex is one of the challenges in structural proteomics. Such a scoring function would open the route to in silico, large-scale annotation and prediction of complete interactomes. Here we present a protein-protein binding affinity benchmark consisting of binding constants (K-d's) for 81 complexes. This benchmark was used to assess the performance of nine commonly used scoring algorithms along with a free-energy prediction algorithm in their ability to predicting binding affinities. Our results reveal a poor correlation between binding affinity and scores for all algorithms tested. However, the diversity and validity of the benchmark is highlighted when binding affinity data are categorized according to the methodology by which they were determined. By further classifying the complexes into low, medium and high affinity groups, significant correlations emerge, some of which are retained after dividing the data into more classes, showing the robustness of these correlations. Despite this, accurate prediction of binding affinity remains outside our reach due to the large associated standard deviations of the average score within each group. All the above-mentioned observations indicate that improvements of existing scoring functions or design of new consensus tools will be required for accurate prediction of the binding affinity of a given protein-protein complex. The benchmark developed in this work will serve as an indispensable source to reach this goal.