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Systematic prediction of human membrane receptor interactions
Author(s) -
Qi Yanjun,
Dhiman Harpreet K.,
Bhola Neil,
Budyak Ivan,
Kar Siddhartha,
Man David,
Dutta Arpana,
Tirupula Kalyan,
Carr Brian I.,
Grandis Jennifer,
BarJoseph Ziv,
KleinSeetharaman Judith
Publication year - 2009
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200900259
Subject(s) - interactome , computational biology , membrane protein , biology , bioinformatics , membrane , biochemistry , gene
Membrane receptor‐activated signal transduction pathways are integral to cellular functions and disease mechanisms in humans. Identification of the full set of proteins interacting with membrane receptors by high‐throughput experimental means is difficult because methods to directly identify protein interactions are largely not applicable to membrane proteins. Unlike prior approaches that attempted to predict the global human interactome, we used a computational strategy that only focused on discovering the interacting partners of human membrane receptors leading to improved results for these proteins. We predict specific interactions based on statistical integration of biological data containing highly informative direct and indirect evidences together with feedback from experts. The predicted membrane receptor interactome provides a system‐wide view, and generates new biological hypotheses regarding interactions between membrane receptors and other proteins. We have experimentally validated a number of these interactions. The results suggest that a framework of systematically integrating computational predictions, global analyses, biological experimentation and expert feedback is a feasible strategy to study the human membrane receptor interactome.