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Coarse-Grained Parallelization of Distance-Bound Smoothing for the Molecular Conformation Problem

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Part of the Lecture Notes in Computer Science book series (LNCS,volume 2571)

Abstract

Determining the three-dimensional structure of proteins is crucial to efficient drug design and understanding biological processes. One successful method for computing the molecule’s shape relies on the inter-atomic distance bounds provided by the Nucleo-Magnetic Resonance (NMR) spectroscopy. The accuracy of computed structures as well as the time required to obtain them are greatly improved if the gaps between the upper and lower distance-bounds are reduced. These gaps are reduced most effectively by applying the tetrangle inequality, derived from the Cayley-Menger determinant, to all atom-quadruples. However, tetrangle-inequality bound-smoothing is an extremely computation intensive task, requiring O(n 4) time for an n-atom molecule. To reduce the computation time, we propose a novel coarse-grained parallel algorithm intended for a Beowulf-type cluster of PCs. The algorithm employs p n/6 processors and requires O(n 4/p) time and O(p 2) communications. The number of communications is at least an order of magnitude lower than in the earlier parallelizations. Our implementation utilized the processors with at least 59% efficiency (including the communication overhead) — an impressive figure for a nonembarrassingly parallel problem on a cluster of workstations.

Keywords

  • Parallel Algorithm
  • Communication Step
  • Distance Geometry
  • Molecular Conformation Problem
  • Early Parallelizations

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. C. B. Anfinsen. Principles that govern the protein folding chains. Science, vol. 181, pp. 233–230, 1973.

    CrossRef  Google Scholar 

  2. A. Aszödi, M. J. Gradwell, W. R. Taylor. Global fold determination from a small number of distance restraints. Journal of Molecular Biology, vol. 251, pp. 308–326, 1995.

    CrossRef  Google Scholar 

  3. D. J. Becker, T. Sterling, D. Savarese, E. Dorband, U. A. Ranawake, C. V. Packer. BEOWULF: A parallel workstation for scientific computation. Proceedings of the 1995 International Conference on Parallel Processing (ICPP), pp. 11–14, 1995.

    Google Scholar 

  4. H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. In. Shindyalov, P. E. Bourne. The Protein Data Bank, Nucleic Acids Research, vol. 28, pp. 235–242, 2000.

    CrossRef  Google Scholar 

  5. L. M. Blumenthal. Theory and Applications of Distance Geometry. Chelsea Publishing Company, Bronx, New York, 1970.

    MATH  Google Scholar 

  6. A. E. Brouwer. Optimal packings of K4’s into a Kn. Journal of Combinatorial Theory, vol. 26, pp. 278–297, 1979.

    MATH  CrossRef  MathSciNet  Google Scholar 

  7. F. E. Cohen, I. D. Kuntz. Tertiary structure prediction. In G. D. Fasman, editor, Prediction of Protein Structure and the Principles of Protein Conformation, pp. 647–705, Plenum Press, New York, 1989.

    Google Scholar 

  8. G. M. Crippen. A novel approach to the calculation of conformation: Distance geometry. Journal of Computational Physiology, vol. 24, pp. 96–107, 1977.

    MATH  MathSciNet  Google Scholar 

  9. G. M. Crippen, T. F. Havel. Distance Geometry and Molecular Conformation. Research Studies Press Ltd., Taunton, Somerset, England, 1988.

    MATH  Google Scholar 

  10. N. Deo, P. Micikevicius. Coarse-grained parallelization of distance-bound smoothing. Computer Science Technical Report CS-TR-02-06, University of Central Florida, 2002.

    Google Scholar 

  11. N. Deo, P. Micikevicius. On cyclic one-factorization of complete 3-uniform hypergraphs. Congressus Numerantium, to appear, 2003.

    Google Scholar 

  12. P. L. Easthope and T. F. Havel. Computational experience with an algorithm for tetrangleinequality bound-smoothing. Bulletin of Mathematical Biology, vol. 51, pp. 173–194, 1989.

    MATH  MathSciNet  Google Scholar 

  13. P. Güntert. Structure calculation of biological macromolecules from NMR data. Quarterly reviews of biophysics, vol. 31, pp. 145–237, 1998.

    CrossRef  Google Scholar 

  14. T. F. Havel. The sampling properties of some distance geometry algorithms applied to unconstrained polypeptide chains: a study of 1830 independently computed conformations. Biopolymers, vol. 29, pp. 1565–1585, 1990.

    CrossRef  Google Scholar 

  15. T. F. Havel. An evaluation of computational strategies for use in the determination of protein structure from distance constraints obtained by nuclear magnetic resonance. Prog. Biophys. Mol. Biol., vol. 56, pp. 43–78, 1991.

    CrossRef  Google Scholar 

  16. B. A. Hendrickson. The molecule problem: Exploiting structure in global optimizations. SIAM Journal on Optimization, vol. 5, pp. 835–857, 1995.

    MATH  CrossRef  MathSciNet  Google Scholar 

  17. N. Kumar, N. Deo, R. Addanki. Empirical study of a tetrangle-inequality boundsmoothing algorithm. Congressus Numerantium, vol. 117, pp. 15–31, 1996.

    MATH  MathSciNet  Google Scholar 

  18. K. Menger. New foundation of Euclidean geometry. Amer. J. Math., vol. 53, pp. 721–45, 1931.

    MATH  CrossRef  MathSciNet  Google Scholar 

  19. P. Micikevicius. Parallel Graph Algorithms for Molecular Conformation and Tree Codes. Ph.D. thesis, University of Central Florida, Orlando, Florida, 2002.

    Google Scholar 

  20. K. Rajan. Parallel Algorithms for the Molecular Conformation Problem. Ph.D. thesis, University of Central Florida, Orlando, Florida, 1999.

    Google Scholar 

  21. K. Rajan, N. Deo. A parallel algorithm for bound-smoothing. Proceedings of the 13 th International Parallel Processing Symposium, April 12-16, San Juan, Puerto Rico, 1999, pp. 645–652.

    Google Scholar 

  22. K. Rajan, N. Deo. Computational experience with a parallel algorithm for tetrangle inequality bound smoothing. Bulletin of Mathematical Biology, vol. 61(5), pp. 987–1008, 1999.

    CrossRef  Google Scholar 

  23. K. Rajan, N. Deo, N. Kumar. Generating disjoint t-(v, k, 1) packings in parallel. Congressus Numerantium, vol. 131, pp. 5–18, 1998.

    MATH  MathSciNet  Google Scholar 

  24. D. K. Searls. Grand challenges in computational biology. In Computational Models in Molecular Biology, S. L. Salzberg, D. K. Searls, S. Kasif, editors. Elsevier, 1998.

    Google Scholar 

  25. M. Snir, S. Otto, S. Huss-Lederman, D. Walker, J. Dongarra. MPI: The Complete Reference. MIT Press, Cambridge, Massachusetts, 1996.

    Google Scholar 

  26. T. Sterling, D. Savarese. A coming of age for Beowulf-class computing. Lecture Notes in Computer Science, vol. 1685, pp. 78–88, 1999.

    Google Scholar 

  27. W. D. Wallis. Combinatorial Designs. Marcel Dekker, Inc., New York, 1998.

    Google Scholar 

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Deo, N., Micikevicius, P. (2002). Coarse-Grained Parallelization of Distance-Bound Smoothing for the Molecular Conformation Problem. In: Das, S.K., Bhattacharya, S. (eds) Distributed Computing. IWDC 2002. Lecture Notes in Computer Science, vol 2571. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36385-8_6

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  • DOI: https://doi.org/10.1007/3-540-36385-8_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00355-7

  • Online ISBN: 978-3-540-36385-9

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