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High-performance workspace for conformational modeling in rational drug design

Keywords:

D.M. Spel'nikov – Junior Research Scientist, National Research University of Information Technologies, Mechanics and Optics
S.N. Knyazev – Researcher, National Research University of Information Technologies, Mechanics and Optics
M.A. Balakhontseva – Post-graduant Student, National Research University of Information Technologies, Mechanics and Optics
M.V. Buzdalov – Post-graduant Student, National Research University of Information Technologies, Mechanics and Optics
Y.B. Porozov – Ph. D. (Med.), National Research University of Information Technologies, Mechanics and Optics, Head of Laboratory
V.G. Maslov – Dr. Sc. (Phys.-Math.), Associate Professor, National Research University of Information Technologies, Mechanics and Optics
A.V. Bukhanovskiy – Dr. Sc. (Eng.), Professor, National Research University of Information Technologies, Mechanics and Optics


The high-performance workspace for protein conformational modeling is discussed. There are three stages of the calculations in the workspace: 1) Protein conformational modeling 2) Docking conformations 3) Interaction analysis The workspace were used for calculations of abl kinase and its mutants conformational properties. The docking and interaction analysis of imatinib, niloatinib and dasatinib were done. In silico experiments show that free binding energy decreases for interactions with mutants. Distributed workspace architecture based on CLAVIRE platform provides flexible tuning for wide range of problems such as homology modeling, docking, rescoring and combining them in workflows. Besides that, Distributed workspace architecture based on CLAVIRE platform provides high potential for scalability in heterogeneous computing environments.
References:

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  2. Accelrys – Scientific Enterprise Software for Chemical Research. www.accelrys.com
  3. CLAVIRE: e-Science infrastructure for data-driven computing / Knyazkov K. V., Kovalchuk S. V., Tchurov T. N., Maryin S. V., Boukhanovsky A. V. // Journal of Computational Science. 2012. T. 3. № 6. P. 504 – 510.
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  5. Yuriev E., Agostino M., Ramsland P. A. Challenges and advances in computational docking: 2009 in review // J. Mol. Recognit. 2011. V. 24. P. 149 – 164.
  6. Hansen N., Muller S. D., Koumoutsakos P. Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) // Evolutionary Computation 11(1). 2003. R. 1 – 18.
  7. GROMACS -A molecular dynamics package primarily designed for biomolecular systems such as proteins and lipids: rezhim dostupa www.gromacs.org.
  8. Vasil'ev V. N., Buxanovskij A. V., Kozlov S. A., Maslov V. G., Rozanov N. N. Vy'sokoproizvoditel'ny'j programmny'j kompleks modelirovaniya nanorazmerny'x atomno-molekulyarny'x sistem // Nauchno-texnicheskij vestnik informaczionny'x texnologij, mexaniki i optiki. 2008. № 54. S. 3 – 12.

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