PDZ Domain Binding Selectivity Is Optimized Across the Mouse Proteome

• Published in: Science (American Association for the Advancement of Science) Vol. 317; no. 5836; pp. 364 - 369
• Main Authors: Stiffler, Michael A, Chen, Jiunn R, Grantcharova, Viara P, Lei, Ying, Fuchs, Daniel, Allen, John E, Zaslavskaia, Lioudmila A, MacBeath, Gavin
• Format: Journal Article
• Language: English
• Published: Washington, DC American Association for the Advancement of Science 20.07.2007; The American Association for the Advancement of Science
• Subjects: Algorithms; Amino Acid Sequence; Amino acids; Animals; Binding sites; Biochemistry; Biological and medical sciences; Computational Biology; Computer Simulation; Cross reaction; Data smoothing; False negative errors; False positive errors; Fluorescence; Fluorescence Polarization; Fundamental and applied biological sciences. Psychology; Interactions. Associations; Intermolecular phenomena; Ligands; Mice; Modeling; Molecular biophysics; Peptides; Peptides - metabolism; Protein Array Analysis; Protein Binding; Protein Structure, Tertiary; Proteins; Proteome - chemistry; Proteome - metabolism; Proteomes; Proteomics; Rodents; Vertebrata; Mammalia; Mouse; Rodentia; Molecular interaction; Proteome; Selectivity
• ISSN: 0036-8075; 1095-9203
• DOI: 10.1126/science.1144592

PDZ domains have long been thought to cluster into discrete functional classes defined by their peptide-binding preferences. We used protein microarrays and quantitative fluorescence polarization to characterize the binding selectivity of 157 mouse PDZ domains with respect to 217 genome-encoded peptides. We then trained a multidomain selectivity model to predict PDZ domain-peptide interactions across the mouse proteome with an accuracy that exceeds many large-scale, experimental investigations of protein-protein interactions. Contrary to the current paradigm, PDZ domains do not fall into discrete classes; instead, they are evenly distributed throughout selectivity space, which suggests that they have been optimized across the proteome to minimize cross-reactivity. We predict that focusing on families of interaction domains, which facilitates the integration of experimentation and modeling, will play an increasingly important role in future investigations of protein function.