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Solving the Protein Threading Problem by Lagrangian Relaxation

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Algorithms in Bioinformatics (WABI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3240))

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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

  1. Head-Gordon, T., Wooley, J.C.: Computational challenges in structural and functional genomics. IBM Systems Journal 40, 265–296 (2001)

    Article  Google Scholar 

  2. 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)

    Chapter  Google Scholar 

  3. 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)

    Chapter  Google Scholar 

  4. Lathrop, R., Smith, T.: Global optimum protein threading with gapped alignment and empirical pair potentials. J. Mol. Biol. 255, 641–665 (1996)

    Article  Google Scholar 

  5. Xu, Y., Xu, D., Uberbacher, E.C.: An efficient computational method for globally optimal threading. Journal of Computational Biology 5, 597–614 (1998)

    Article  Google Scholar 

  6. 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)

    Article  Google Scholar 

  7. Andonov, R., Yanev, N.: Solving the protein threading problem in parallel. In: HiCOMB 2003 – Second IEEE International Workshop on High Performance Computational Biology (2003)

    Google Scholar 

  8. Andonov, R., Balev, S., Yanev, N.: Protein threading: From mathematical models to parallel implementations. INFORMS Journal on Computing (2004) (to appear)

    Google Scholar 

  9. Marin, A., Pothier, J., Zimmermann, K., Gibrat, J.F.: FROST: a filter-based fold recognition method. Proteins 49, 493–509 (2002)

    Article  Google Scholar 

  10. 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)

    Google Scholar 

  11. Lathrop, R.: The protein threading problem with sequence amino acid interaction preferences is NP-complete. Protein Engineering 7, 1059–1068 (1994)

    Article  Google Scholar 

  12. Akutsu, T., Miyano, S.: On the approximation of protein threading. Theoretical Computer Science 210, 261–275 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  13. Nemhauser, G.L., Wolsey, L.A.: Integer and Combinatorial Optimization. Wiley, Chichester (1988)

    MATH  Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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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

  • Online ISBN: 978-3-540-30219-3

  • eBook Packages: Springer Book Archive

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