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CUSA and CUDE: GPU-accelerated methods for estimating solvent accessible surface area and desolvation

David Dynerman, Erick Butzlaff, Julie C. Mitchell
Department of Mathematics, University of Wisconsin, Madison, Wisconsin
Journal of computational biology: a journal of computational molecular cell biology, Vol. 16, No. 4. (April 2009), pp. 523-537.

@article{dynerman2009cusa,

   title={CUSA and CUDE: GPU-accelerated methods for estimating solvent accessible surface area and desolvation},

   author={Dynerman, D. and Butzlaff, E. and Mitchell, J.C.},

   journal={Journal of Computational Biology},

   volume={16},

   number={4},

   pages={523–537},

   year={2009},

   publisher={Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA}

}

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It is well-established that a linear correlation exists between accessible surface areas and experimentally measured solvation energies. Combining this knowledge with an analytic formula for calculation of solvent accessible surfaces, we derive a simple model of desolvation energy as a differentiable function of atomic positions. Additionally, we find that this algorithm is particularly well suited for hardware acceleration on graphics processing units (GPUs), outperforming the CPU by up to two orders of magnitude. We explore the scaling of this desolvation algorithm and provide implementation details applicable to general pairwise algorithms.
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