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GPGPU-assisted prediction of ion binding sites in proteins

Leonid Uroshlev, Sergei Rahmanov, Ivan Kulakovskiy, Vsevolod Makeev
IOGen, Moscow, Russian Federation
International Moscow Conference on Computational Molecular Biology (MCCMB’11), 2011

@article{uroshlev2011gpgpu,

   title={GPGPU-assisted prediction of ion binding sites in proteins},

   author={Uroshlev, L. and Rahmanov, S. and Kulakovskiy, I. and Makeev, V.},

   journal={Department of Bioengineering and Bioinformatics of MV Lomonosov Moscow State University},

   pages={375},

   year={2011}

}

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Prediction of binding sites for different types of ions in protein 3D structure context is a complex challenge for biophysical computational methods. One possible approach involves using empirical, also called as knowledge-based, potentials. In the current study, we present a new GPGPU program complex, PIONCA (Protein-ION CAlculator) for efficient generation of empirical potentials for protein-ion interaction, provide description of its characteristics, and also present a publically available online service based on it.
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