PLoS Computational Biology (Dec 2011)

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

  • Amin R Mazloom,
  • Ruth Dannenfelser,
  • Neil R Clark,
  • Arsen V Grigoryan,
  • Kathryn M Linder,
  • Timothy J Cardozo,
  • Julia C Bond,
  • Aislyn D W Boran,
  • Ravi Iyengar,
  • Anna Malovannaya,
  • Rainer B Lanz,
  • Avi Ma'ayan

DOI
https://doi.org/10.1371/journal.pcbi.1002319
Journal volume & issue
Vol. 7, no. 12
p. e1002319

Abstract

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Coregulator proteins (CoRegs) are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP) followed by mass spectrometry (MS) applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.