Title: Faculty Opinions recommendation of PDZ domain binding selectivity is optimized across the mouse proteome.
Abstract: 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. PMID: 17641200 Funding information This work was supported by: NIGMS NIH HHS, United States Grant ID: 5 T32 GM07598-25 NIGMS NIH HHS, United States Grant ID: 1 RO1 GM072872-01 NIGMS NIH HHS, United States Grant ID: R01 GM072872-04 NIGMS NIH HHS, United States Grant ID: R01 GM072872