maisМоделирование и анализ информационных системModeling and Analysis of Information Systems1818-10152313-5417Yaroslavl State University10.18255/1818-1015-2014-5-93-101mais-87Research ArticleОригинальные статьиArticlesПрименение методов оптимизации для выполнения молекулярного докинга на графических процессорахApplication of Numerical Optimization Methods to Perform Molecular Docking on Graphics Processing UnitsФарковМихаил АлександровичFarkovM. A.

аспирант, Россия, 660041, г. Красноярск, пр. Свободный, 79

аспирант, Svobodny pr., Krasnoyarsk, 660041, Russia

mihail.farkov@gmail.comЛегаловАлександр ИвановичLegalovA. I.

профессор, заведующий кафедрой вычислительной техники, Россия, 660041, г. Красноярск, пр. Свободный, 79

профессор, заведующий кафедрой вычислительной техники, Svobodny pr., Krasnoyarsk, 660041, Russia

legalov@mail.ruСибирский Федеральный УниверситетРоссияSiberian Federal UniversityRussian Federation20142010201421593101Copyright © Фарков М.А., Легалов А.И., 20142014Фарков М.А., Легалов А.И.Farkov M.A., Legalov A.I.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.mais-journal.ru/jour/article/view/87

В работе проведён анализ методов оптимизации для решения задачи молекулярного докинга. Сформированы дополнительные требования, предъявляемые к методам оптимизации при их реализации на графических процессорах. Выбран перспективный метод для графических процессоров и продемонстрирована его реализация.

An analysis of numerical optimization methods for solving a problem of molecular docking has been performed. Some additional requirements for optimization methods according to GPU architecture features were specified. A promising method for implementation on GPU was selected. Its implementation was described and performance and accuracy tests were performed.

CUDAGPGPUмолекулярный докингвиртуальный скрининглиганд-белковый докингдифференциальная эволюцияGPGPUCUDAmolecular dockingvirtual screeningligand-protein dockingReferencesФарков М.А. Вычисление сеток взаимодействия молекул с использованием графических процессоров // Исследования наукограда. 2013. 3(5), июль–сентябрь. C. 49–52.Фарков М.А. Вычисление сеток взаимодействия молекул с использованием графических процессоров // Исследования наукограда. 2013. 3(5), июль–сентябрь. C. 49–52.Trott O., Olson A. AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading // Journal Computational Chemistry. 2010. 31. P. 455–461.Trott O., Olson A. AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading // Journal Computational Chemistry. 2010. 31. P. 455–461.Jones G., Willett P., Glen R., Leach A., Taylor R. Development and Validation of a Genetic Algorithm for Flexible Docking // Journal of Molecular Biology. 1997. 267. P. 727–748.Jones G., Willett P., Glen R., Leach A., Taylor R. Development and Validation of a Genetic Algorithm for Flexible Docking // Journal of Molecular Biology. 1997. 267. P. 727–748.Stroganov O.V., Novikov F., Stroylov V., Kulkov V., Chilov G. Lead finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening // Journal of Chemical Information and Modeling. 2008. 48(12). P. 2371–2385.Stroganov O.V., Novikov F., Stroylov V., Kulkov V., Chilov G. Lead finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening // Journal of Chemical Information and Modeling. 2008. 48(12). P. 2371–2385.Liu M., Wang S. MCDOCK: A Monte Carlo simulation approach to the molecular docking problem // Journal of Computer-Aided Molecular Design. 1999. 13. P. 435–451.Liu M., Wang S. MCDOCK: A Monte Carlo simulation approach to the molecular docking problem // Journal of Computer-Aided Molecular Design. 1999. 13. P. 435–451.Meiler J., Baker D. ROSETTALIGAND: Protein–Small Molecule Docking with Full SideChain Flexibility // PROTEINS: Structure, Function, and Bioinformatics. 2006. 65. P. 538–548.Meiler J., Baker D. ROSETTALIGAND: Protein–Small Molecule Docking with Full SideChain Flexibility // PROTEINS: Structure, Function, and Bioinformatics. 2006. 65. P. 538–548.Korb O., Stutzle T., Exner T.E. Accelerating molecular docking calculations using graphics processing units // Journal of chemical information and modeling. American Chemical Society. 2011. 51(4). P. 865–876.Korb O., Stutzle T., Exner T.E. Accelerating molecular docking calculations using graphics processing units // Journal of chemical information and modeling. American Chemical Society. 2011. 51(4). P. 865–876.Storn R., Price K. Differential evolution – A simple and efficient heuristic for global optimization over continuous spaces // Journal of Global Optimization. 1997. 11(4). P. 341–359.Storn R., Price K. Differential evolution – A simple and efficient heuristic for global optimization over continuous spaces // Journal of Global Optimization. 1997. 11(4). P. 341–359.Pechan I., Feher B. Hardware Accelerated Molecular Docking: A Survey // Bioinformatics. ISBN 978-953-51-0878-8. Available from: http://www.intechopen.com/books/bioinformatics/hardware-accelerated-molecular-docking-a-surveyPechan I., Feher B. Hardware Accelerated Molecular Docking: A Survey // Bioinformatics. ISBN 978-953-51-0878-8. Available from: http://www.intechopen.com/books/bioinformatics/hardware-accelerated-molecular-docking-a-surveyMorris G.M., Huey R., Lindstrom W., Sanner M.F., Belew R.K., Goodsel, D.S., Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility // Journal of Computational Chemistry. 2009. 30. P. 2785–2791.Morris G.M., Huey R., Lindstrom W., Sanner M.F., Belew R.K., Goodsel, D.S., Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility // Journal of Computational Chemistry. 2009. 30. P. 2785–2791.Morris G.M., Goodsell D.S., Halliday R.S., Huey R., Hart W.E., Belew R.K., Olson A.J. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function // Journal of Computational Chemistry. 1998. 19. P. 1639–1662.Morris G.M., Goodsell D.S., Halliday R.S., Huey R., Hart W.E., Belew R.K., Olson A.J. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function // Journal of Computational Chemistry. 1998. 19. P. 1639–1662.Farkov M.A. Calculation of force field grids for molecular docking using GPU // Journal of Siberian Federal University. Biology. 2014. 7(1). P. 4–13.Farkov M.A. Calculation of force field grids for molecular docking using GPU // Journal of Siberian Federal University. Biology. 2014. 7(1). P. 4–13.

The authors declare that there are no conflicts of interest present.