Systematic prediction of human membrane receptor interactions

Yanjun Qi[1]1, Harpreet K. Dhiman2, Neil Bhola3, Ivan Budyak4, Siddhartha Kar5, David Man2, Arpana Dutta2, Kalyan Tirupula2, Brian I. Carr5, Jennifer Grandis3,  Ziv Bar-Joseph1§ and Judith Klein-Seetharaman1,2,4§


@ PROTEOMICS (2009)  (Published: 1 Oct 2009,9,5243-5255) & PDF version

==> ISMB 2010 Highlighted Task : talk slide PDF


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.



Supplementary Files (also in PROTEOMICS ):

·        S0-Table of Contents.pdf

·        S1-Computational Methods.pdf

·        S2-Computational Results.pdf

·        S3-Experimental Methods.pdf

·        S4-Analysis & Visualization.pdf

·        S5-Web Server HMRI.pdf

·        S6-PredictedReceptorInteractomeRFcut1.xls  (S6 is the list of predicted human membrane receptor interactions in EXCEL spread sheet format. It includes both RF scores and p-values for each predicted pair)



Other global analyses of HMRI (besides contents of above six supp-documents; HMRI: human membrane receptor interactome): 


·        Module analysis of the predicted receptor interactome (from biclustering)

·        Download bicluster modules

·        Graph properties analysis of the predicted receptor interactome

·        Subgraphs of HMRI in Cytoscape format (could directly import into Cytoscape for Visualization)

·        Multiple kinds of hub protein lists of the predicted HMRI (cutoff 2.0)



Predictions Download (predicted interaction scores for all human membrane receptors)


·        Gene list of human membrane receptors and their associated family information

·        About the download: README  (each receptor has its own predicted interaction score file)

==> Downloading List of All Prediction Files per Receptor

·        File directory I  to download all prediction files  (files larger than 2M)  - README

·        File directory II  to download all prediction files  (files smaller than 2M)  - README

·        Prediction File format readme

·        Here we provide another file including the predicted scores for all potential pairs (receptor to human proteins): Predicted RF Scores for all potential receptor to human protein pairs (Format: GeneID1,GeneID2,RFscore)

·        Related useful gene lists

·        Predicted human membrane receptor interactome with cutoff 2.0 (Cytoscape fileformat)



Software Download (both source-code and runnable versions provided):


·        A software could be used to predict any sub-network of the human protein-protein interactions (based on user provided human protein list)

·        A Java based GUI interface version and a perl based command-line batch version are provided.

·        Software download

        + Random-Forest-Perl-Wrapper developed along this paper

·        Software Manual



Web Service HMRI :


·        To enable other biomedical researchers to benefit from our human membrane receptor interactome, we have implemented our method as a web server “HMRI

·        (

·        An interactive interface has been created that allows users the retrieval of interactions. Researchers interested in specific membrane receptors can enter individual or sets of proteins and retrieve their rank-ordered interactions, along with the evidence supporting these predictions.

(sorry. The "web service" site is down currently due the machine problem. You can access all of our predictions from the above file downloading link.)



·        Affiliations: 

1School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA

2Department of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA

3Department of Otolaryngology, Eye and Ear Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA  15260, USA

4Institute for Structural Biology (IBI-2), Research Center Jülich 52425, Germany

5Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA

§ contact authors






* Current Address: NEC Labs America Inc, 4 Independence Way, Princeton, NJ 08540, USA