Document Detail


Discovering interacting domains and motifs in protein-protein interactions.
MedLine Citation:
PMID:  23192537     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Many important biological processes, such as the signaling pathways, require protein-protein interactions (PPIs) that are designed for fast response to stimuli. These interactions are usually transient, easily formed, and disrupted, yet specific. Many of these transient interactions involve the binding of a protein domain to a short stretch (3-10) of amino acid residues, which can be characterized by a sequence pattern, i.e., a short linear motif (SLiM). We call these interacting domains and motifs domain-SLiM interactions. Existing methods have focused on discovering SLiMs in the interacting proteins' sequence data. With the recent increase in protein structures, we have a new opportunity to detect SLiMs directly from the proteins' 3D structures instead of their linear sequences. In this chapter, we describe a computational method called SLiMDIet to directly detect SLiMs on domain interfaces extracted from 3D structures of PPIs. SLiMDIet comprises two steps: (1) interaction interfaces belonging to the same domain are extracted and grouped together using structural clustering and (2) the extracted interaction interfaces in each cluster are structurally aligned to extract the corresponding SLiM. Using SLiMDIet, de novo SLiMs interacting with protein domains can be computationally detected from structurally clustered domain-SLiM interactions for PFAM domains which have available 3D structures in the PDB database.
Authors:
Willy Hugo; Wing-Kin Sung; See-Kiong Ng
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Methods in molecular biology (Clifton, N.J.)     Volume:  939     ISSN:  1940-6029     ISO Abbreviation:  Methods Mol. Biol.     Publication Date:  2013  
Date Detail:
Created Date:  2012-11-29     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9214969     Medline TA:  Methods Mol Biol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  9-20     Citation Subset:  IM    
Affiliation:
School of Computing, National University of Singapore, Singapore, Singapore.
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