Automated docking with grid-based energy evaluation
Journal of Computational Chemistry
gprof: a call graph execution profiler
ACM SIGPLAN Notices - Best of PLDI 1979-1999
A Fast Wavelet Based Implementation to Calculate Coulomb Potentials on the Cell/B.E.
HPCC '08 Proceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
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The completion of the human genome project has brought new and still unprocessed information about potential targets for the treatment of human diseases with drugs. The efficacy of a drug can be vastly improved through the interaction with multiple targets, although undesirable side effects must also be studied. Experimental approaches for this purpose are very expensive and time consuming, while in-silico approaches can efficiently propose accurate predictions that drastically reduce testing procedures in the laboratory. Nevertheless, in-silico approaches for multiple target identification have not been yet fully explored and most of them still deal with rigid receptor models. It has been shown recently that the docking program FlexScreen includes efficiently protein flexibility. However, processing large databases of target proteins is a very time consuming process. In a new optimization approach, massively parallel architectures like GPUs can greatly overcome these limitations. In this study we report our FlexScreen parallelization efforts using CUDA.