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Fast and accurate protein substructure searching with simulated annealing and GPUs

Alex D. Stivala, Peter J. Stuckey, Anthony I. Wirth
Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia
BMC bioinformatics, Vol. 11, No. 1. (2010), 446.

@article{stivala2010fast,

   title={Fast and accurate protein substructure searching with simulated annealing and GPUs},

   author={Stivala, A.D. and Stuckey, P.J. and Wirth, A.I.},

   journal={BMC bioinformatics},

   volume={11},

   number={1},

   pages={446},

   issn={1471-2105},

   year={2010},

   publisher={BioMed Central Ltd}

}

BACKGROUND: Searching a database of protein structures for matches to a query structure, or occurrences of a structural motif, is an important task in structural biology and bioinformatics. While there are many existing methods for structural similarity searching, faster and more accurate approaches are still required, and few current methods are capable of substructure (motif) searching. RESULTS: We developed an improved heuristic for tableau-based protein structure and substructure searching using simulated annealing, that is as fast or faster and comparable in accuracy, with some widely used existing methods. Furthermore, we created a parallel implementation on a modern graphics processing unit (GPU). CONCLUSIONS: The GPU implementation achieves up to 34 times speedup over the CPU implementation of tableau-based structure search with simulated annealing, making it one of the fastest available methods. To the best of our knowledge, this is the first application of a GPU to the protein structural search problem.
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