Effect of the sequence data deluge on the performance of methods for detecting protein functional residues

BMC Bioinformatics
Diego Garrido-Martín, Florencio Pazos

Abstract

The exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely. In this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performa...Continue Reading

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Methods Mentioned

BETA
sequence-based prediction

Software Mentioned

Clustal
ClustalW
Two Entropies Analysis Objective ( TEA - O )
Evolutionary Trace ( ET )
Xdet
S3det
TEA
BLAST
FireDB
Clustal Omega

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