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Improving pairwise comparison of protein sequences with domain co-occurrence

Christophe Menichelli, Olivier Gascuel, Laurent Bréhélin
doi: https://doi.org/10.1101/115543
Christophe Menichelli
1Computational biology institute, LIRMM, Univ. Montpellier, CNRS, 860 Rue de St-Priest, 34095 Montpellier Cede× 5, France
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  • For correspondence: christophe.menichelli@lirmm.fr
Olivier Gascuel
1Computational biology institute, LIRMM, Univ. Montpellier, CNRS, 860 Rue de St-Priest, 34095 Montpellier Cede× 5, France
2Unité de Bioinformatique Evolutive, C3BI - USR 3756, Institut Pasteur et CNRS,, Paris, France
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Laurent Bréhélin
1Computational biology institute, LIRMM, Univ. Montpellier, CNRS, 860 Rue de St-Priest, 34095 Montpellier Cede× 5, France
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Abstract

Motivation Comparing and aligning protein sequences is an essential task in bioinformatics. More specifically, local alignment tools like BLAST are widely used for identifying conserved protein sub-sequences, which likely correspond to protein domains or functional motifs. However, to limit the number of false positives, these tools are used with stringent sequence-similarity thresholds and hence can miss several hits, especially for species that are phylogenetically distant from reference organisms. A solution to this problem is then to integrate additional contextual information to the procedure.

Results Here, we propose to use domain co-occurrence to increase the sensitivity of pairwise sequence comparisons. Domain co-occurrence is a strong feature of proteins, since most protein domains tend to appear with a limited number of other domains on the same protein. We propose a method to take this information into account in a typical BLAST analysis and to construct new domain families on the basis of these results. We used Plasmodium falciparum as a case study to evaluate our method. The experimental findings showed an increase of 16% of the number of significant BLAST hits and an increase of 28% of the proteome area that can be covered with a domain. Our method identified 2473 new domains for which, in most cases, no model of the Pfam database could be linked. Moreover, our study of the quality of the new domains in terms of alignment and physicochemical properties show that they are close to that of standard Pfam domains.

Availability Software implementing the proposed approach and the Supplementary Data are available at: https://gite.lirmm.fr/menichelli/pairwise-comparison-with-cooccurrence

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 09, 2017.
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Improving pairwise comparison of protein sequences with domain co-occurrence
Christophe Menichelli, Olivier Gascuel, Laurent Bréhélin
bioRxiv 115543; doi: https://doi.org/10.1101/115543
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Improving pairwise comparison of protein sequences with domain co-occurrence
Christophe Menichelli, Olivier Gascuel, Laurent Bréhélin
bioRxiv 115543; doi: https://doi.org/10.1101/115543

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