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Molecular Distance Geometry Optimization Using Geometric Build-up and Evolutionary Techniques on GPU

Levente Fabry-Asztalos, Istvan Lorentz, Razvan Andonie
Department of Chemistry, Central Washington University, Ellensburg, WA, USA
IEEE Symposium on Computational Intelligence and Computational Biology (CIBCB 2012), 2012

@article{fabry2012molecular,

   title={Molecular Distance Geometry Optimization Using Geometric Build-up and Evolutionary Techniques on GPU},

   author={Fabry-Asztalos, L. and Lorentz, I. and Andonie, R.},

   year={2012}

}

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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 buildup method reconstructs the 3D structures with a root-meansquare error (RMSE) in the order of 0.1 A. 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 A 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.
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