• DocumentCode
    3646918
  • Title

    Molecular distance geometry optimization using geometric build-up and evolutionary techniques on GPU

  • Author

    Levente Fabry-Asztalos;István Lőrentz;Răzvan Andonie

  • Author_Institution
    Department of Chemistry, Central Washington University, Ellensburg, USA
  • fYear
    2012
  • Firstpage
    321
  • Lastpage
    328
  • Abstract
    We present a combination of methods addressing the molecular distance problem, implemented on a graphic processing unit. First, we use geometric build-up and depth-first graph traversal. Next, we refine the solution by simulated annealing. For an exact but sparse distance matrix, the build-up method reconstructs the 3D structures with a root-mean-square error (RMSE) in the order of 0.1 Å. Small and medium structures (up to 10,000 atoms) are computed in less than 10 seconds. For the largest structures (up to 100,000 atoms), the build-up RMSE is 2.2 Å and execution time is about 540 seconds. The performance of our approach depends largely on the graph structure. The SA step improves accuracy of the solution to the expense of a computational overhead.
  • Keywords
    "Complexity theory","Simulated annealing","Proteins","Vectors","Geometry","Graphics processing unit","Chemicals"
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2012 IEEE Symposium on
  • Print_ISBN
    978-1-4673-1190-8
  • Type

    conf

  • DOI
    10.1109/CIBCB.2012.6217247
  • Filename
    6217247