Prediction of functional sites from protein multiple sequence alignments
Author(s): Jonathan Manning and Emily Jefferson and Geoff Barton
Affiliations: University of Dundee
Keywords: 'protein' 'alignment' 'function' 'site'
We detail a new method for the prediction of functionally significant positions in multiple sequence alignments, named SMERFS. The algorithm exploits patterns present in the homology relationships of protein multiple sequence alignments to propose functionally significant regions. However in contrast to many other techniques based on this premise, SMERFS requires neither fixed subgrouping nor phylogenetic tree. We validate the method using structurally derived data, present some preliminary evaluation by comparison to hierarchical analysis methods  and conventional conservation measures , and discuss future prospects.
1. Zvelebil, M.J., et al., Prediction of protein secondary structure and active sites using the alignment of homologous sequences. J Mol Biol, 1987. 195(4): p. 957-61.
2. Livingstone, C.D. and G.J. Barton, Protein sequence alignments: a strategy for the hierarchical analysis of residue conservation. Comput Appl Biosci, 1993. 9(6): p. 745-56.
3. Lichtarge, O., H.R. Bourne, and F.E. Cohen, An evolutionary trace method defines binding surfaces common to protein families. J Mol Biol, 1996. 257(2): p. 342-58.
4. Armon, A., D. Graur, and N. Ben-Tal, ConSurf: an algorithmic tool for the identification of functional regions in proteins by surface mapping of phylogenetic information. J Mol Biol, 2001. 307(1): p. 447-63.
5. La, D. and D.R. Livesay, Predicting functional sites with an automated algorithm suitable for heterogeneous datasets. BMC Bioinformatics, 2005. 6(1): p. 116.
6. Valdar, W.S., Scoring residue conservation. Proteins, 2002. 48(2): p. 227-41.