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
Link To Document :
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