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Journal of Computer-Aided Molecular Design

, Volume 33, Issue 1, pp 119–127 | Cite as

Monte Carlo on the manifold and MD refinement for binding pose prediction of protein–ligand complexes: 2017 D3R Grand Challenge

  • Mikhail Ignatov
  • Cong Liu
  • Andrey Alekseenko
  • Zhuyezi Sun
  • Dzmitry Padhorny
  • Sergei Kotelnikov
  • Andrey Kazennov
  • Ivan Grebenkin
  • Yaroslav Kholodov
  • Istvan Kolosvari
  • Alberto Perez
  • Ken Dill
  • Dima KozakovEmail author
Article
  • 130 Downloads

Abstract

Manifold representations of rotational/translational motion and conformational space of a ligand were previously shown to be effective for local energy optimization. In this paper we report the development of the Monte-Carlo energy minimization approach (MCM), which uses the same manifold representation. The approach was integrated into the docking pipeline developed for the current round of D3R experiment, and according to D3R assessment produced high accuracy poses for Cathepsin S ligands. Additionally, we have shown that (MD) refinement further improves docking quality. The code of the Monte-Carlo minimization is freely available at https://bitbucket.org/abc-group/mcm-demo.

Keywords

Manifold Monte Carlo MD Minimization D3R Cathepsin S 

Notes

Acknowledgements

This work was supported by Grants NIH R21 GM127952, NIH R01 GM12581301, NSF AF 1816314, NSF AF 1645512 and RSF No 14-11-00877.

Supplementary material

10822_2018_176_MOESM1_ESM.pdf (127 kb)
Supplementary material 1 (PDF 126 KB)

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Mikhail Ignatov
    • 1
    • 2
    • 3
    • 7
  • Cong Liu
    • 2
  • Andrey Alekseenko
    • 6
    • 7
  • Zhuyezi Sun
    • 5
  • Dzmitry Padhorny
    • 1
    • 2
    • 3
    • 7
  • Sergei Kotelnikov
    • 1
    • 2
    • 3
    • 4
    • 7
  • Andrey Kazennov
    • 4
    • 7
  • Ivan Grebenkin
    • 6
    • 7
  • Yaroslav Kholodov
    • 6
    • 7
  • Istvan Kolosvari
    • 5
  • Alberto Perez
    • 2
  • Ken Dill
    • 2
  • Dima Kozakov
    • 1
    • 2
    • 3
    Email author
  1. 1.Department of Applied Mathematics and StatisticsStony Brook UniversityStony BrookUSA
  2. 2.Laufer Center for Physical and Quantitative BiologyStony Brook UniversityStony BrookUSA
  3. 3.Institute for Advanced Computational SciencesStony Brook UniversityStony BrookUSA
  4. 4.Moscow Institute of Physics and TechnologyMoscowRussia
  5. 5.Department of Biomedical EngineeringBoston UniversityBostonUSA
  6. 6.Innopolis UniversityInnopolisRussia
  7. 7.Institute for Computer-Aided DesignRussian Academy of SciencesMoscowRussia

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