Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes

Sriganesh Srihari, Chern Han Yong, Ashwini Patil, Limsoon Wong

Research output: Contribution to journalReview articlepeer-review

48 Citations (Scopus)


Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area.

Original languageEnglish
Pages (from-to)2590-2602
Number of pages13
JournalFEBS Letters
Issue number19
Publication statusPublished or Issued - 14 Sep 2015


  • Complexes in diseases
  • Dynamic and fuzzy complexes
  • PPI network
  • Protein complex prediction

ASJC Scopus subject areas

  • Biophysics
  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Genetics
  • Cell Biology

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