Genome-Wide Prediction of SH2 Domain Targets Using Structural Information and the FoldX Algorithm

TY - JOUR

T1 - Genome-Wide Prediction of SH2 Domain Targets Using Structural Information and the FoldX Algorithm

AU - Sanchez, Ignacio E.

AU - Beltrao, Pedro

AU - Stricher, Francois

AU - Schymkowitz, Joost

AU - Ferkinghoff-Borg, Jesper

AU - Rousseau, Frederic

AU - Serrano, Luis

PY - 2008

Y1 - 2008

N2 - Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly to experimentally derived consensus sequences and substitution matrices at predicting known in vitro and in vivo targets of SH2 domains. We use our method to provide a set of high-confidence interactions for human SH2 domains with known structure filtered on secondary structure and phosphorylation state. We validated the predictions using literature-derived SH2 interactions and a probabilistic score obtained from a naive Bayes integration of information on coexpression, conservation of the interaction in other species, shared interaction partners, and functions. We show how our predictions lead to a new hypothesis for the role of SH2 domains in signaling

AB - Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly to experimentally derived consensus sequences and substitution matrices at predicting known in vitro and in vivo targets of SH2 domains. We use our method to provide a set of high-confidence interactions for human SH2 domains with known structure filtered on secondary structure and phosphorylation state. We validated the predictions using literature-derived SH2 interactions and a probabilistic score obtained from a naive Bayes integration of information on coexpression, conservation of the interaction in other species, shared interaction partners, and functions. We show how our predictions lead to a new hypothesis for the role of SH2 domains in signaling

U2 - 10.1371/journal.pcbi.1000052

DO - 10.1371/journal.pcbi.1000052

M3 - Journal article

VL - 4

SP - e1000052

JO - P L o S Computational Biology (Online)

JF - P L o S Computational Biology (Online)

SN - 1553-7358

IS - 4

ER -