Knowledge-guided inference of domain-domain interactions from incomplete protein-protein interaction networks

Bioinformatics. 2009 Oct 1;25(19):2492-9. doi: 10.1093/bioinformatics/btp480. Epub 2009 Aug 10.

Abstract

Motivation: Protein-protein interactions (PPIs), though extremely valuable towards a better understanding of protein functions and cellular processes, do not provide any direct information about the regions/domains within the proteins that mediate the interaction. Most often, it is only a fraction of a protein that directly interacts with its biological partners. Thus, understanding interaction at the domain level is a critical step towards (i) thorough understanding of PPI networks; (ii) precise identification of binding sites; (iii) acquisition of insights into the causes of deleterious mutations at interaction sites; and (iv) most importantly, development of drugs to inhibit pathological protein interactions. In addition, knowledge derived from known domain-domain interactions (DDIs) can be used to understand binding interfaces, which in turn can help discover unknown PPIs.

Results: Here, we describe a novel method called K-GIDDI (knowledge-guided inference of DDIs) to narrow down the PPI sites to smaller regions/domains. K-GIDDI constructs an initial DDI network from cross-species PPI networks, and then expands the DDI network by inferring additional DDIs using a divide-and-conquer biclustering algorithm guided by Gene Ontology (GO) information, which identifies partial-complete bipartite sub-networks in the DDI network and makes them complete bipartite sub-networks by adding edges. Our results indicate that K-GIDDI can reliably predict DDIs. Most importantly, K-GIDDI's novel network expansion procedure allows prediction of DDIs that are otherwise not identifiable by methods that rely only on PPI data.

Availability: http://www.ittc.ku.edu/~xwchen/domainNetwork/ddinet.html

Publication types

  • Research Support, N.I.H., Intramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Binding Sites
  • Computational Biology / methods*
  • Databases, Protein
  • Protein Interaction Domains and Motifs*
  • Protein Interaction Mapping / methods*