| Literature DB >> 17641200 |
Michael A Stiffler1, Jiunn R Chen, Viara P Grantcharova, Ying Lei, Daniel Fuchs, John E Allen, Lioudmila A Zaslavskaia, Gavin MacBeath.
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.Entities:
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Year: 2007 PMID: 17641200 PMCID: PMC2674608 DOI: 10.1126/science.1144592
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728