Predicting PDZ domain-peptide interactions from primary sequences.
Predicting PDZ domain-peptide interactions from primary sequences.
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DOI：
10.1038/nbt.1489
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发表时间：
2008-09
影响因子：
1.5
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中科院分区：
文献类型：
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PDZ结构域是最大的相互作用结构域家族之一，通过结合靶蛋白的C端发挥作用。利用贝叶斯估计，我们构建了一个位置特异性评分矩阵的三维扩展，根据PDZ结构域和肽的主要序列，预测PDZ结构域将与哪些肽结合。该模型使用小鼠基因组中82个PDZ结构域和93个编码肽的相互作用数据进行训练，成功预测了涉及其他小鼠PDZ结构域的相互作用，以及来自黑腹果蝇的PDZ结构域，以及在较小程度上来自秀丽隐杆线虫的PDZ结构域。该模型还预测了肽配体的点突变对其PDZ结构域结合亲和力的不同影响。总的来说，我们表明我们的方法在单个模型中捕获了PDZ结构域家族的结合选择性。
PDZ domains constitute one of the largest families of interaction domains and function by binding the C termini of their target proteins. Using Bayesian estimation, we constructed a three-dimensional extension of a position-specific scoring matrix that predicts to which peptides a PDZ domain will bind, given the primary sequences of the PDZ domain and the peptides. The model, which was trained using interaction data from 82 PDZ domains and 93 peptides encoded in the mouse genome, successfully predicts interactions involving other mouse PDZ domains, as well as PDZ domains from Drosophila melanogaster and, to a lesser extent, PDZ domains from Caenorhabditis elegans. The model also predicts the differential effects of point mutations in peptide ligands on their PDZ domain–binding affinities. Overall, we show that our approach captures, in a single model, the binding selectivity of the PDZ domain family.