HomPPI: a class of sequence homology based protein-protein interface prediction methods.
HomPPI: a class of sequence homology based protein-protein interface prediction methods.
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DOI：
10.1186/1471-2105-12-244
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发表时间：
2011-06-17
影响因子：
3
通讯作者：
Honavar V
中科院分区：
文献类型：
--
作者：
Xue LC;Dobbs D;Honavar V
尽管基于同源性的方法是预测蛋白质结构和功能最广泛使用的方法之一，但界面序列守恒是否可以有效地用于预测蛋白质-蛋白质界面的问题一直是争论的主题。我们研究了30多万个蛋白质序列的成对比对，这些蛋白质序列来自于结构特征的蛋白质复合物，包括专性和瞬态复合物。我们确定了查询蛋白序列中基于界面残基的准确同源推断所需的序列相似性标准。基于这些分析，我们开发了HomPPI，这是一类基于序列同源性的预测蛋白质-蛋白质界面残基的方法。我们提出了HomPPI的两种变体：(i) NPS-HomPPI（非伴侣特异性HomPPI），可用于在不知道相互作用伴侣的情况下预测查询蛋白的界面残基；（ii） PS-HomPPI (Partner-specific HomPPI)，可用于预测查询蛋白与特定靶蛋白的界面残基。我们在专性二聚体复合物的基准数据集上的实验表明，当查询蛋白的序列同源性能够可靠地识别时，NPS-HomPPI可以可靠地预测给定蛋白质中的蛋白质-蛋白质界面残基，平均相关系数（CC）为0.76，灵敏度为0.83，特异性为0.78。NPS-HomPPI还能可靠地预测内在无序蛋白的界面残基。我们的实验表明，NPS-HomPPI可以与几种最先进的界面预测服务器竞争，包括那些利用查询蛋白结构的服务器。伴侣特异性分类器PS-HomPPI可以在一个大的瞬态复合物数据集上预测具有特定靶标的查询蛋白的界面残基，当查询和靶标的同源物都可以可靠地识别时，CC为0.65，灵敏度为0.69，特异性为0.70。HomPPI web服务器可在http://homppi.cs.iastate.edu/上获得。基于序列同源性的方法为预测参与专性或瞬时相互作用的蛋白质-蛋白质界面残基提供了一类计算效率高且可靠的方法。对于参与瞬态相互作用的查询蛋白，利用假定相互作用伙伴的知识可以提高界面残馀预测的可靠性。
Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/. Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners.
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影响因子：
3
作者：
Cho YR;Zhang A
通讯作者：
Zhang A
影响因子：
64.8
作者：
CHOTHIA, C;JANIN, J
通讯作者：
JANIN, J
影响因子：
2.9
作者：
Chen, HL;Zhou, HX
通讯作者：
Zhou, HX
影响因子：
2.9
作者：
Chakrabarti, P;Janin, J
通讯作者：
Janin, J
影响因子：
5.6
作者：
Armon, A;Graur, D;Ben-Tal, N
通讯作者：
Ben-Tal, N