TTDock: a docking method based on tensor train decompositions

Authors

  • D.A. Zheltkov
  • I.V. Oferkin
  • A.V. Sulimov
  • V.B. Sulimov
  • E.V. Katkova
  • E.E. Tyrtyshnikov

Keywords:

tensor train decomposition
cross interpolation method
global optimization
docking
computer drug design

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.

New computational technologies

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Published

2013-06-20

Issue

Vol. 14 (2013): Issue 3.

Section

Section 1. Numerical methods and applications

Author Biographies

D.A. Zheltkov

Lomonosov Moscow State University,
Faculty of Computational Mathematics and Cybernetics
• PhD Student

I.V. Oferkin

Dimonta, LLC
• Programmer

A.V. Sulimov

Dimonta, LLC
• System Programmer

V.B. Sulimov

Lomonosov Moscow State University,
Faculty of Computational Mathematics and Cybernetics
• Head of Laboratory

E.V. Katkova

Dimonta, LLC
• Junior Researcher

E.E. Tyrtyshnikov

Institute of Numerical Mathematics of RAS (INM RAS)
• Director

References

  1. Садовничий В.А., Сулимов В.Б. Суперкомпьютерные технологии в медицине // Суперкомпьютерные технологии в науке, образовании и промышленности / Под ред. В.А. Садовничего, Г.И. Савина, Вл.В. Воеводина. М: Изд-во Моск. ун-та, 2009. 16-23.
  2. Романов А.Н., Кондакова О.А., Григорьев Ф.В., Сулимов A.В., Лущекина С.В., Мартынов Я.Б., Сулимов В.Б. Компьютерный дизайн лекарственных средств: программа докинга SOL // Вычислительные методы и программирование. 2008. 9. 213-233.
  3. Офёркин И.В., Сулимов А.В., Кондакова О.А., Сулимов В.Б. Реализация поддержки параллельных вычислений в программах докинга SOLGRID и SOL // Вычислительные методы и программирование. 2011. 12. 9-23.
  4. Mobley D.L., Dill K.A. Binding of small-molecule ligands to proteins: «what you see» is not always «what you get» // Structure. 2009. 17, N 4. 489-498.
  5. Kolda T.G., Bader B.W. Tensor decompositions and applications // SIAM Review. 2009. 51, N 3. 455-500.
  6. Oseledets I.V., Savostianov D.V., Tyrtyshnikov E.E. Tucker dimensionality reduction of three-dimensional arrays in linear time // SIAM J. Matrix Anal. Appl. 2008. 30, N 3. 939-956.
  7. Oseledets I.V., Tyrtyshnikov E.E. Breaking the curse of dimensionality, or how to use SVD in many dimensions // SIAM J. Sci. Comput. 2009. 31, N 5. 3744-3759.
  8. Oseledets I.V. Tensor-train decomposition // SIAM J. Sci. Comput. 2011. 33, N 5. 2295-2317.
  9. Oseledets I.V., Tyrtyshnikov E.E. TT-cross approximation for multidimensional arrays // Linear Algebra Appl. 2010. 432, N 1. 70-88.
  10. Goreinov S.A., Tyrtyshnikov E.E., Zamarashkin N.L. A theory of pseudo-skeleton approximations // Linear Algebra Appl. 1997. 261, N 1-3. 1-21.
  11. Tyrtyshnikov E.E. Incomplete cross approximation in the mosaic-skeleton method // Computing. 2000. 64, N 4. 367-380.
  12. Goreinov S.A., Tyrtyshnikov E.E. The maximal-volume concept in approximation by low-rank matrices // Contemporary Mathematics. 2001. 208. 47-51.
  13. Goreinov S.A., Oseledets I.V., Savostyanov D.V., Tyrtyshnikov E.E., Zamarashkin N.L. How to find a good submatrix // Matrix Methods: Theory, Algorithms, Applications / Edited by V. Olshevsky and E. Tyrtyshnikov. Hackensack: World Scientific, 2010. 247-256.
  14. Huey R., Morris G.M., Olson A.J., Goodsell D.S. A semiempirical free energy force field with charge-based desolvation // J. Computational Chemistry. 2007. 28, N 6. 1145-1152.
  15. Verdonk M.L., Cole J.C., Hartshorn M.J., Murray C.W., Taylor R.D. Improved protein-ligand docking using GOLD // Proteins: Structure, Function, and Bioinformatics. 2003. 52, N 4. 609-623.
  16. Thomsen R., Christensen M.H. MolDock: a new technique for high-accuracy molecular docking // J. Medicinal Chemistry. 2006. 49, N 11. 3315-3321.
  17. Halgren T.A. Merck molecular force field // J. Computational Chemistry. 1996. 17, N 5/6. 490-519.
  18. Romanov A.N., Jabin S.N., Martynov Y.B., Sulimov A.V., Grigoriev F.V., Sulimov V.B. Surface generalized Born method: a simple, fast, and precise implicit solvent model beyond the Coulomb approximation // J. Physical Chemistry A. 2004. 108, N 43. 9323-9327.
  19. RCSB protein data bank (http://www.rcsb.org/pdb/home/home.do).
  20. Alvarez J., Shoichet B. Virtual screening in drug discovery. Vol. 1. Boca Raton: CRC Press, 2005.
  21. CSAR 2011-2012 Benchmark Exercise (http://www.csardock.org/).

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