Abstract
This paper presents an efficient algorithm for aligning aquery amino-acid sequence to a protein 3D structure template. Solving this problem is one of the main steps of the methods of protein structure prediction by threading. We propose an integer programming model and solve it by branch-and-bound algorithm. The bounds are computed using a Lagrangian dual of the model which turns out to be much easier to solve than its linear programming relaxation. The Lagrangian relaxations are computed using a dynamic programming algorithm. The experimental results show that our algorithm outperforms the commonly used methods. The proposed algorithm is general enough and can be easily plugged in most of the threading tools in order to increase their performance.
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References
Head-Gordon, T., Wooley, J.C.: Computational challenges in structural and functional genomics. IBM Systems Journal 40, 265–296 (2001)
Lengauer, T.: Computational biology at the beginning of the post-genomic era. In: Wilhelm, R. (ed.) Informatics: 10 Years Back, 10 Years Ahead. LNCS, vol. 2000, pp. 341–355. Springer, Heidelberg (2001)
Lathrop, R., Rogers Jr., R., Bienkowska, J., Bryant, B., Buturovic, L., Gaitatzes, C., Nambudripad, R., White, J., Smith, T.: Analysis and algorithms for protein sequence-structure alignment. In: Salzberg, S., Searls, D., Kasif, S. (eds.) Computational Methods in Molecular Biology, pp. 227–283. Elsevier Science, Amsterdam (1998)
Lathrop, R., Smith, T.: Global optimum protein threading with gapped alignment and empirical pair potentials. J. Mol. Biol. 255, 641–665 (1996)
Xu, Y., Xu, D., Uberbacher, E.C.: An efficient computational method for globally optimal threading. Journal of Computational Biology 5, 597–614 (1998)
Xu, J., Li, M., Lin, G., Kim, D., Xu, Y.: RAPTOR: optimal protein threading by linear programming. Journal of Bioinformatics and Computational Biology 1, 95–118 (2003)
Andonov, R., Yanev, N.: Solving the protein threading problem in parallel. In: HiCOMB 2003 – Second IEEE International Workshop on High Performance Computational Biology (2003)
Andonov, R., Balev, S., Yanev, N.: Protein threading: From mathematical models to parallel implementations. INFORMS Journal on Computing (2004) (to appear)
Marin, A., Pothier, J., Zimmermann, K., Gibrat, J.F.: FROST: a filter-based fold recognition method. Proteins 49, 493–509 (2002)
Marin, A., Pothier, J., Zimmermann, K., Gibrat, J.F.: Protein threading statistics: an attempt to assess the significance of a fold assignment to a sequence. In: Tsigelny, I. (ed.) Protein structure prediction: bioinformatic approach, International University Line (2002)
Lathrop, R.: The protein threading problem with sequence amino acid interaction preferences is NP-complete. Protein Engineering 7, 1059–1068 (1994)
Akutsu, T., Miyano, S.: On the approximation of protein threading. Theoretical Computer Science 210, 261–275 (1999)
Nemhauser, G.L., Wolsey, L.A.: Integer and Combinatorial Optimization. Wiley, Chichester (1988)
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Balev, S. (2004). Solving the Protein Threading Problem by Lagrangian Relaxation. In: Jonassen, I., Kim, J. (eds) Algorithms in Bioinformatics. WABI 2004. Lecture Notes in Computer Science(), vol 3240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30219-3_16
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DOI: https://doi.org/10.1007/978-3-540-30219-3_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23018-2
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