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Computational experience with a parallel algorithm for tetrangle inequality bound smoothing.

K Rajan1, N Deo

  • 1School of Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA. dharmara@longwood.cs.ucf.edu

Bulletin of Mathematical Biology
|September 25, 2007
PubMed
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This study introduces a parallel algorithm for molecular structure determination using tetrangle inequalities. The new method efficiently refines interatomic distance bounds, improving computational speed for complex molecules.

Area of Science:

  • Computational chemistry
  • Structural biology
  • Bioinformatics

Background:

  • Determining molecular structure from interatomic distances is crucial but challenging.
  • Nuclear Magnetic Resonance (NMR) provides distance bounds for a limited number of atom pairs.
  • Existing methods for refining these bounds, like triangle inequality, have limitations.

Purpose of the Study:

  • To develop an efficient algorithm for bound smoothing of interatomic distances.
  • To improve the accuracy of molecular structure determination using available distance constraints.
  • To leverage parallel computing for faster bound smoothing.

Main Methods:

  • Utilizing the tetrangle inequality, expressed by Cayley-Menger determinants, for bound smoothing.
  • Developing a parallel algorithm for applying tetrangle inequalities across all atom quadruples.

Related Experiment Videos

  • Implementing and analyzing the performance of the parallel algorithm on an Intel Paragon XP/S system.

    • Main Results:

    • The proposed parallel algorithm achieves O(n^3 log n) time complexity on a REW PRAM with O(n log n) processors.
    • This represents a significant speedup compared to the O(n^4) complexity of sequential tetrangle inequality application.
    • Performance analysis of the implementation on the Intel Paragon XP/S is provided.

    Conclusions:

    • The parallel algorithm offers a computationally efficient approach to bound smoothing for molecular structure determination.
    • This method enhances the refinement of interatomic distance bounds, aiding in structural analysis.
    • The study demonstrates the practical application and performance benefits of parallel computing in this domain.