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

Srihari, Sriganesh, Han Yong, Chern, Patil, Ashwini and Wong, Limsoon (2015) Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes. FEBS Letters, 589 19: 2590-2602. doi:10.1016/j.febslet.2015.04.026

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Author Srihari, Sriganesh
Han Yong, Chern
Patil, Ashwini
Wong, Limsoon
Title Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes
Journal name FEBS Letters   Check publisher's open access policy
ISSN 1873-3468
0014-5793
Publication date 2015-01-01
Year available 2015
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1016/j.febslet.2015.04.026
Open Access Status File (Author Post-print)
Volume 589
Issue 19
Start page 2590
End page 2602
Total pages 13
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Language eng
Subject 1304 Biophysics
1315 Structural Biology
1303 Biochemistry
1312 Molecular Biology
1311 Genetics
1307 Cell Biology
Abstract 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.
Keyword Protein complexes
Protein interaction network
Complexes in diseases
Dynamic and fuzzy complexes
PPI network
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID 1028742
Institutional Status UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: Official 2016 Collection
Institute for Molecular Bioscience - Publications
 
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Created: Sat, 02 May 2015, 19:05:45 EST by Sriganesh Srihari on behalf of Institute for Molecular Bioscience