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Parallel Supercomputer Docking Program of the New Generation: Finding Low Energy Minima Spectrum

  • Alexey Sulimov
  • Danil Kutov
  • Vladimir SulimovEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 965)

Abstract

The results of studies of the energy surfaces of the protein-ligand complexes carried out with the help of the FLM docking program belonging to the new generation of gridless docking programs are presented. It is demonstrated that the ability of the FLM docking program to find the global energy minimum is much higher than one of the “classical” SOL docking program using the genetic algorithm and the preliminary calculated grid of potentials of ligand atoms interactions with the target protein. The optimal number of FLM local optimization reliable finding of the global energy minimum and all local minima with energies in the 2 kcal/mol interval above the energy of the global minimum is found. This number is 250 thousand. For complexes with the ligand containing more than 60 atoms and having more than 12 torsions and with more than protein 4500 protein atoms the number of FLM local optimizations should be noticeably increased. There are several unique energy minima in this energy interval and for most complexes these minima are located near (RMSD < 3 \( {\AA} \)) the global minimum. However, there a complexes where such minima are located far from the global minimum with RMSD (on all ligand atoms) > 5  \( {\AA} \).

Keywords

Generalized docking Local optimization Global minimum Low-energy local minima spectrum High-performance computing Molecular modeling Drug design 

Notes

Acknowledgements

The work was financially supported by the Russian Science Foundation, Agreement no. 15-11-00025-П. The research is carried out using the equipment of the shared research facilities of HPC computing resources at Lomonosov Moscow State University, including the Lomonosov supercomputer [24].

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexey Sulimov
    • 1
    • 2
  • Danil Kutov
    • 1
    • 2
  • Vladimir Sulimov
    • 1
    • 2
    Email author
  1. 1.Dimonta, Ltd.MoscowRussia
  2. 2.Research Computer CenterLomonosov Moscow State UniversityMoscowRussia

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