Clustering of protein domains for functional and evolutionary studies.

Pavle Goldstein 1 Jurica Zucko 2, 3 Dušica Vujaklija 4 Anita Kriško 5, 6 Daslav Hranueli 3 Paul Long 7 Catherine Etchebest 8 Bojan Basrak 1 John Cullum 2, *
* Auteur correspondant
1 Department of Mathematics
2 Department of Genetics
3 Faculty of Food Technology and Biotechnology
4 Department of Molecular Biology
5 Génétique moléculaire, évolutive et médicale
6 Mediterranean Institute for Life Sciences
7 The School of Pharmacy
8 Bioinformatique génomique et moléculaire
Abstract : BACKGROUND: The number of protein family members defined by DNA sequencing is usually much larger than those characterised experimentally. This paper describes a method to divide protein families into subtypes purely on sequence criteria. Comparison with experimental data allows an independent test of the quality of the clustering. RESULTS: An evolutionary split statistic is calculated for each column in a protein multiple sequence alignment; the statistic has a larger value when a column is better described by an evolutionary model that assumes clustering around two or more amino acids rather than a single amino acid. The user selects columns (typically the top ranked columns) to construct a motif. The motif is used to divide the family into subtypes using a stochastic optimization procedure related to the deterministic annealing EM algorithm (DAEM), which yields a specificity score showing how well each family member is assigned to a subtype. The clustering obtained is not strongly dependent on the number of amino acids chosen for the motif. The robustness of this method was demonstrated using six well characterized protein families: nucleotidyl cyclase, protein kinase, dehydrogenase, two polyketide synthase domains and small heat shock proteins. Phylogenetic trees did not allow accurate clustering for three of the six families. CONCLUSION: The method clustered the families into functional subtypes with an accuracy of 90 to 100%. False assignments usually had a low specificity score.
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BMC Bioinformatics, BioMed Central, 2009, 10 (1), pp.335. 〈10.1186/1471-2105-10-335〉
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Pavle Goldstein, Jurica Zucko, Dušica Vujaklija, Anita Kriško, Daslav Hranueli, et al.. Clustering of protein domains for functional and evolutionary studies.. BMC Bioinformatics, BioMed Central, 2009, 10 (1), pp.335. 〈10.1186/1471-2105-10-335〉. 〈inserm-00663929〉

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