D. A. Zheltkov, I. V. Oferkin, E. V. Katkova, A. V. Sulimov, V. B. Sulimov, E. E. Tyrtyshnikov, “TTDock: a docking method based on tensor train decompositions”, Num. Meth. Prog., 2013, Volume 14, Issue 3,Pages <nobr>279

This article is cited in 3 papers

Вычислительные методы и приложения

TTDock: a docking method based on tensor train decompositions

D. A. Zheltkov^a, I. V. Oferkin^b, E. V. Katkova^b, A. V. Sulimov^b, V. B. Sulimov^c, E. E. Tyrtyshnikov^d

^a M. V. Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics
^b Dimonta Ltd.
^c M.V. Lomonosov Moscow State University, Research Computing Center
^d Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow

Abstract: A new docking method based on tensor train decomposition is proposed. This method allows one to find the position of the energy global minimum for the ligand-protein system with a high probability. The proposed method is compared with one of the best genetic algorithm docking program SOL. According to the testing results, the docking method based on tensor train decompositions is up to 10 times faster, whereas the energy global optimum is reached with the same probability.

Keywords: tensor train decomposition; cross interpolation method; global optimization; docking; computer drug design.

UDC: 519.6

Received: 09.05.2013