Systematic prediction of human membrane receptor interactions

Yanjun Qi, Harpreet K. Dhiman, Neil Bhola, Ivan Budyak, Siddhartha Kar, David Man, Arpana Dutta, Kalyan Tirupula, Brian I. Carr, Jennifer Grandis, Ziv Bar-Joseph, Judith Klein-Seetharaman

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)5243-5255
Number of pages13
Issue number23
StatePublished - Dec 2009
Externally publishedYes


  • Data integration
  • Membrane proteins
  • Protein-protein interaction network
  • Receptor crosstalk
  • Receptor interactome
  • Signal transduction
  • Systems biology

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology


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