Abstract
We present in this paper a peptide matching approach to the multiple comparison of a set of protein sequences. This approach consists in looking for all the words that are common to q of these sequences, where q is a parameter.
The comparison between words is done by using as reference an object called a model. In the case of proteins, a model is a product of subsets of the alphabet σ of the amino acids. These subsets belong to a cover of σ, that is, their union covers all of σ. A word is said to be an instance of a model if it belongs to the model.
A further flexibility is introduced in the comparison by allowing for up to e errors in the comparison between a word and a model. A word is said to be this time an occurrence of a model if the Levenshtein distance between it and an instance of the model is inferior or equal to e. Two words are said to be similar if there is at least one model of which both are occurrences. In the special case where e = 0, the occurrences of a model are simply its instances. If a model M has occurrences in at least q of the sequences of the set, M is said to occur in the set.
The algorithm presented here is an efficient and exact way of looking for all the models, of a fixed length k or of the greatest possible length k max , that occur in a set of sequences. It is linear in the total length n of the sequences and proportional to k 2e+1 where k ≪ n is a small value in all practical situations.
Models are closely related to what is called a consensus in the biocomputing area, and covers are a good way of representing complex relationships between the amino acids.
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References
G.J. Barton and M.J.E. Sternberg. A strategy for the rapid multiple alignment of protein sequences: confidence levels from tertiary structure comparisons. J. Mol. Biol., 198:327–337, 1987.
D.L. Brutlag, J-P. Dautricourt, S. Maulik, and J. Relph. Improved sensitivity of biological sequence database searches. Comput. Applic. Biosc., 6:237–245, 1990.
H. Carrillo and D.J. Lipman. The multiple sequence alignment problem in biology. SIAM J. Appl. Math., 48:1073–1083, 1988.
A.L. Cobbs. Fast identification of approximately matching substrings. In M. Crochemore and D. Gusfield, editors, Combinatorial Pattern Matching, pages 64–74. Springer Verlag, 1994.
M.O. Dayhoff, R.M. Schwartz, and B.C. Orcutt. A model of evolutionary change in proteins. In M.O. Dayhoff, editor, Atlas of Protein Sequence an Structure, volume 5 suppl.3, pages 345–352. Natl. Biomed. Res. Found., 1978.
D.F. Feng and R.F. Doolittle. Progressive sequence alignment as a prerequisite to correct phylogenetic trees. J. Mol. Evol., 25:351–360, 1987.
D. Gusfield. Efficient method for multiple sequence alignment with guaranteed error bounds. Bull. of Math. Biol., 55:141–154, 1993.
S. Henikoff. Comparative sequence analysis: finding genes. In D.W. Smith, editor, Biocomputing. Informatics and Genome Projects, pages 87–117. Academic Press, 1994.
S. Henikoff and J.G. Henikoff. Automated assembly of protein blocks for database searching. Nucl. Acids Res., 19:6565–6572, 1991.
S. Karlin and G. Ghandour. Multiple alphabet amino acid sequence comparisons of the immunoglobulin k-chain constant domain. Proc. Natl. Acad. Sci. USA, 82:8597–8601, 1985.
R.M. Karp, R.E. Miller, and A.L. Rosenberg. Rapid identification of repeated patterns in strings, trees and arrays. pages 125–136. Proc. 4th Annu. ACM Symp. Theory of Computing, 1972.
A. Landraud, J.F. Avril, and P. Chretienne. An algorithm for finding a common structure shared by a family of strings. IEEE Trans. on Pattern Analysis and Machine Intelligence, 11:890–895, 1989.
H.M. Martinez. A flexible multiple sequence alignment program. Nucleic Acids Res., 16:1683–1691, 1988.
R.N. Pau. Nitrogenases without molybdenum. Trends Biochem. Sci., 14:183–186, 1989.
J. Posfai, A.S. Bhagwat, G. Posfai, and R.J. Roberts. Prediction motifs derived from cytosine methyltransferases. Nucl. Acids Res., 17:2421–2435, 1989.
M. F. Sagot, A. Viari, J. Pothier, and H. Soldano. Finding flexible patterns in a text — an application to 3D molecular matching. pages 117–145, Seattle, Washington, USA, 1994. First International IEEE Workshop on Shape and Pattern Matching in Computational Biology.
M.F. Sagot, V. Escalier, A. Viari, and H. Soldano. Searching for repeated words in a text allowing for mismatches and gaps. Viñas del Mar, Chili, 1994. Second South American Workshop on String Processing.
D. Sankoff. Minimum mutation trees of sequences. SIAM J. Appl. Math., 28:35–42, 1975.
D. Sankoff and R.J. Cedergreen. Simultaneous comparison of three or more sequences related by a tree. In D. Sankoff and J.B. Kruskall, editors, Time Warps, String Edits, and Macromolecules. The Theory and Practice of sequence Comparison, pages 253–263. Addison-Wesley, 1983.
G.D. Schuler, S.F. Altschul, and D.J. Lipman. A workbench for multiple alignment construction and analysis. Proteins: Struct., Func., and Genetics, 9:180–190, 1991.
H. Soldano, A. Viari, and M. Champesme. Searching for flexible repeated patterns using a non transitive similarity relation. Pattern Recognition Letters, 1994. in press.
S. Subbiah and S.C. Harrison. A method for multiple sequence alignment with gaps. J. Mol Biol., 209:539–548, 1989.
W.R. Taylor. The classification of amino acid conservation. J. Theor. Biol., 119:205–218, 1986.
A. Viari and J. Pothier. SmartMulti: a tool for the multiple alignment of protein sequences using flexible blocks. Atelier de BioInformatique, 11, rue P. et M. Curie — 75005 Paris, 1994. in preparation.
A.K.C. Wong, S.C. Chan, and D.K.Y. Chiu. A multiple sequence comparison method. Bull. Math. Biol., 55:465–486, 1993.
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Sagot, MF., Viari, A., Soldano, H. (1995). Multiple sequence comparison: A peptide matching approach. In: Galil, Z., Ukkonen, E. (eds) Combinatorial Pattern Matching. CPM 1995. Lecture Notes in Computer Science, vol 937. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60044-2_55
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DOI: https://doi.org/10.1007/3-540-60044-2_55
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