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Bioinformatics. 2012 Jun 1;28(11):1438-45. doi: 10.1093/bioinformatics/bts149. Epub 2012 Mar 30.

Large-scale analysis of conserved rare codon clusters suggests an involvement in co-translational molecular recognition events.

Author information

1
Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 12e Avenue Nord, Sherbrooke, Québec, Canada.

Abstract

MOTIVATION:

An increasing amount of evidence from experimental and computational analysis suggests that rare codon clusters are functionally important for protein activity. Most of the studies on rare codon clusters were performed on a limited number of proteins or protein families. In the present study, we present the Sherlocc program and how it can be used for large scale protein family analysis of evolutionarily conserved rare codon clusters and their relation to protein function and structure. This large-scale analysis was performed using the whole Pfam database covering over 70% of the known protein sequence universe. Our program Sherlocc, detects statistically relevant conserved rare codon clusters and produces a user-friendly HTML output.

RESULTS:

Statistically significant rare codon clusters were detected in a multitude of Pfam protein families. The most statistically significant rare codon clusters were predominantly identified in N-terminal Pfam families. Many of the longest rare codon clusters are found in membrane-related proteins which are required to interact with other proteins as part of their function, for example in targeting or insertion. We identified some cases where rare codon clusters can play a regulating role in the folding of catalytically important domains. Our results support the existence of a widespread functional role for rare codon clusters across species. Finally, we developed an online filter-based search interface that provides access to Sherlocc results for all Pfam families.

AVAILABILITY:

The Sherlocc program and search interface are open access and are available at http://bcb.med.usherbrooke.ca

PMID:
22467916
PMCID:
PMC3465090
DOI:
10.1093/bioinformatics/bts149
[Indexed for MEDLINE]
Free PMC Article

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