Abstract Motivation The development of proteomic methods for the characterization of domain/motif interactions has greatly expanded our understanding of signal transduction. However, proteomics-based binding screens have limitations including that the queried tissue or cell type may not harbor all potential interacting partners or post-translational modifications (PTMs) required for the interaction. Therefore, we sought a generalizable, complementary in silico approach to identify potentially novel motif and PTM-dependent binding partners of high priority. Results We used as an initial example the interaction between the SH2 domains of the adaptor proteins CRK and CRKL and phosphorylated-YXXP motifs. Employing well-curated, publicly-available resources, we scored and prioritized potential CRK/CRKL-SH2 interactors possessing signature characteristics of known interacting partners. Our approach gave high priority scores to 102 of the more than 9,000 YXXP motif-containing proteins. Within this 102 were 21 of the 25 curated CRK/CRKL-SH2 binding partners showing a more than 80-fold enrichment. Several predicted interactors were validated biochemically. To demonstrate generalized applicability, we used our workflow to predict protein-protein interactions dependent upon motif-specific arginine methylation. Our data demonstrate the applicability of our approach to, conceivably, any modular binding domain that recognizes a specific post-translationally modified motif. Contact firstname.lastname@example.org Supplementary Information Supplementary data are available at Bioinformatics Online. © The Author(s) (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
Bioinformatics – Oxford University Press
Published: Jun 1, 2018
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