Functional neighbors: Inferring relationships between nonhomologous protein families using family-specific packing motifs

Deepak Bandyopadhyay, Jun Huan, Jinze Liu, Jan Prins, Jack Snoeyink, Wei Wang, Alexander Tropsha

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


We describe a new approach for inferring the functional relationships between nonhomologous protein families by looking at statistical enrichment of alternative function predictions in classification hierarchies such as Gene Ontology (GO) and Structural Classification of Proteins (SCOP). Protein structures are represented by robust graph representations, and the fast frequent subgraph mining algorithm is applied to protein families to generate sets of family-specific packing motifs, i.e., amino acid residue-packing patterns shared by most family members but infrequent in other proteins. The function of a protein is inferred by identifying in it motifs characteristic of a known family. We employ these family-specific motifs to elucidate functional relationships between families in the GO and SCOP hierarchies. Specifically, we postulate that two families are functionally related if one family is statistically enriched by motifs characteristic of another family, i.e., if the number of proteins in a family containing a motif from another family is greater than expected by chance. This function-inference method can help annotate proteins of unknown function, establish functional neighbors of existing families, and help specify alternate functions for known proteins.

Original languageEnglish
Article number5491173
Pages (from-to)1137-1143
Number of pages7
JournalIEEE Transactions on Information Technology in Biomedicine
Issue number5
StatePublished - Sep 2010

Bibliographical note

Funding Information:
Manuscript received February 15, 2009; revised July 22, 2009; accepted May 6, 2010. Date of publication June 21, 2010; date of current version September 3, 2010. This work was supported by the National Science Foundation under Grant CCF-0523875. The work of J. Prins, J. Snoeyink, W. Wang, and A. Trop-sha was supported by the National Institutes of Health under Grant GM068665. W. Wang gratefully acknowledges support from the National Science Foundation under Grant IIS-0448392.


  • Delaunay tessellation
  • Gene Ontology (GO)
  • Structural Classification of Proteins (SCOP)
  • enrichment evaluation
  • frequent subgraph mining
  • functional neighbors
  • protein structure
  • remote homology

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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