Hu Hai, Columbus John, Zhang Yi, Wu Dongying, Lian Lubing, Yang Song, Goodwin Jennifer, Luczak Christine, Carter Mark, Chen Lin, James Michael, Davis Roger, Sudol Marius, Rodwell John, Herrero Juan J
AxCell Biosciences, Newtown, PA 18940, USA.
Proteomics. 2004 Mar;4(3):643-55. doi: 10.1002/pmic.200300632.
WW domains are protein modules that bind proline-rich ligands. WW domain-ligand complexes are of importance as they have been implicated in several human diseases such as muscular dystrophy, cancer, hypertension, Alzheimer's, and Huntington's diseases. We report the results of a protein array aimed at mapping all the human WW domain protein-protein interactions. Our biochemical approach integrates parallel synthesis of peptides, protein expression, and high-throughput screening methodology combined with tools of bioinformatics. The results suggest that the majority of the bioinformatically predicted WW peptide ligands and most WW domains are functional, and that only about 10% of the measured domain-ligand interactions are positive. The analysis of the WW domain protein arrays also underscores the importance of the amino acid residues surrounding the WW ligand core motifs for specific binding to WW domains. In addition, the methodology presented here allows for the rapid elucidation of WW domain-ligand interactions with multiple applications including prediction of exact WW ligand binding sites, which can be applied to the mapping of other protein signaling domain families. Such information can be applied to the generation of protein interaction networks and identification of potential drug targets. To our knowledge, this report describes the first protein-protein interaction map of a domain in the human proteome.
WW结构域是结合富含脯氨酸配体的蛋白质模块。WW结构域-配体复合物很重要,因为它们与多种人类疾病有关,如肌肉萎缩症、癌症、高血压、阿尔茨海默病和亨廷顿病。我们报告了一项旨在绘制所有人类WW结构域蛋白质-蛋白质相互作用图谱的蛋白质阵列研究结果。我们的生化方法整合了肽的平行合成、蛋白质表达、高通量筛选方法以及生物信息学工具。结果表明,大多数通过生物信息学预测的WW肽配体和大多数WW结构域具有功能,并且所测量的结构域-配体相互作用中只有约10%是阳性的。对WW结构域蛋白质阵列的分析还强调了WW配体核心基序周围氨基酸残基对于与WW结构域特异性结合的重要性。此外,这里介绍的方法允许快速阐明WW结构域-配体相互作用,并具有多种应用,包括预测精确的WW配体结合位点,这可应用于绘制其他蛋白质信号结构域家族的图谱。此类信息可应用于生成蛋白质相互作用网络和识别潜在的药物靶点。据我们所知,本报告描述了人类蛋白质组中一个结构域的首个蛋白质-蛋白质相互作用图谱。