Fast and accurate modeling of protein-protein interactions by combining template-interface-based docking with flexible refinement.
Fast and accurate modeling of protein-protein interactions by combining template-interface-based docking with flexible refinement.
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DOI：
10.1002/prot.24022
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发表时间：
2012-04
期刊：
影响因子：
2.9
通讯作者：
Gursoy A
中科院分区：
文献类型：
--
作者：
Tuncbag N;Keskin O;Nussinov R;Gursoy A
折叠和结合之间的相似性使我们假设自然界中蛋白质-蛋白质界面基序的数量是有限的，相互作用的蛋白质对可以重复使用类似的界面结构，即使它们的全局折叠完全不同。因此，已知的蛋白质-蛋白质界面结构可用于在蛋白质组尺度上模拟两个目标蛋白质之间的复合体，即使它们的全局结构不同。这一强大的概念与灵活的精细化和全球能源评估工具相结合。该方法的准确性高度依赖于模板数据集中接口体系结构的多样性。在此，我们在对接基准上验证了这种基于知识的组合方法，并表明即使在没有与目标具有序列相似性的模板接口的情况下，它也能有效地为基准复合体及其结合区域找到高质量的模型。与“经典”对接相比，它的计算速度更快；随着目标蛋白质数量的增加，差异变得更加戏剧性。此外，它能够区分粘结剂和非粘结剂。这些功能允许执行大规模网络建模。在一个独立的目标集(P53分子相互作用图中的蛋白质)上的结果表明，当前的方法可以用来预测给定的蛋白质对是否相互作用。总体而言，虽然受到模板集多样性的限制，但该方法有效地生成了高质量的蛋白质-蛋白质复合体模型。我们预计，随着已知接口体系结构的数量不断增加，这种基于知识的方法将越来越多地被广泛的蛋白质组学社区使用。
The similarity between folding and binding led us to posit the concept that the number of protein–protein interface motifs in nature is limited, and interacting protein pairs can use similar interface architectures repeatedly, even if their global folds completely vary. Thus, known protein–protein interface architectures can be used to model the complexes between two target proteins on the proteome scale, even if their global structures differ. This powerful concept is combined with a flexible refinement and global energy assessment tool. The accuracy of the method is highly dependent on the structural diversity of the interface architectures in the template dataset. Here, we validate this knowledge-based combinatorial method on the Docking Benchmark and show that it efficiently finds high-quality models for benchmark complexes and their binding regions even in the absence of template interfaces having sequence similarity to the targets. Compared to “classical” docking, it is computationally faster; as the number of target proteins increases, the difference becomes more dramatic. Further, it is able to distinguish binders from nonbinders. These features allow performing large-scale network modeling. The results on an independent target set (proteins in the p53 molecular interaction map) show that current method can be used to predict whether a given protein pair interacts. Overall, while constrained by the diversity of the template set, this approach efficiently produces high-quality models of protein–protein complexes. We expect that with the growing number of known interface architectures, this type of knowledge-based methods will be increasingly used by the broad proteomics community.
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影响因子：
5.8
作者：
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通讯作者：
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