Journal Article

PreJuSER-8400

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Systematic prediction of human membrane receptor interactions

Qi, Y. ; Dhiman, H. K. ; Bhola, N. E. ; Budyak, I. ; Kar, S. ; Man, D. ; Dutta, A. ; Tirupula, K. ; Carr, B. ; Grandis, J. R. ; Bar-Joseph, Z. ; Klein-Seetharaman, J.FZJ*

2009
Wiley VCH Weinheim

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Please use a persistent id in citations: doi:10.1002/pmic.200900259

Abstract: 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.

Keyword(s): Computational Biology: methods (MeSH) ; Humans (MeSH) ; Protein Interaction Mapping: methods (MeSH) ; Proteome: analysis (MeSH) ; Proteome: metabolism (MeSH) ; Proteomics: methods (MeSH) ; Receptor, Epidermal Growth Factor: analysis (MeSH) ; Receptor, Epidermal Growth Factor: metabolism (MeSH) ; Receptors, Cell Surface: analysis (MeSH) ; Receptors, Cell Surface: metabolism (MeSH) ; Signal Transduction (MeSH) ; Systems Biology: methods (MeSH) ; Proteome ; Receptors, Cell Surface ; EGFR protein, human ; Receptor, Epidermal Growth Factor ; J ; Data integration (auto) ; Membrane proteins (auto) ; Protein-protein interaction network (auto) ; Receptor interactome (auto) ; Receptor crosstalk (auto) ; Signal transcluction (auto) ; Systems biology (auto)

Note: This work was supported in part by National Science Foundation Grants ITR 0225656, CAREER 0448453 and CAREER CC044917, National Institutes of Health Grants NLM108730, R01 CA098372 and AI060422 and the Sofya Kovalvskaya Award (to J. K. S.) from the Humboldt Foundation.

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Contributing Institute(s):

1. Molekulare Biophysik (ISB-2)

Research Program(s):

1. Programm Biosoft (N03)

Appears in the scientific report 2009

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Database coverage:
; JCR ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection

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