Parametrization of the Elastic Network Model Using High-Throughput Parallel Molecular Dynamics Simulations

Authors

  • Philipp S. Orekhov 1) Moscow Institute of Physics and Technology, Dolgoprudny, Russia 2) Sechenov University, Moscow, Russia 3) M.V. Lomonosov Moscow State University, Moscow, Russia
  • Ilya V. Kirillov Moscow Institute of Physics and Technology, Dolgoprudny, Russia
  • Vladimir A. Fedorov M.V. Lomonosov Moscow State University, Moscow, Russia
  • Ilya B. Kovalenko 1) M.V. Lomonosov Moscow State University, Moscow, Russia 2) Federal Research and Clinical Center of Specialized Medical Care and Medical Technologies, Federal Medical and Biological Agency of Russia, Moscow, Russia 3) Astrakhan State University, Astrakhan, Russia 4) Scientic and Technological Center of Unique Instrumentation, RAS, Moscow, Russia
  • Nikita B. Gudimchuk 1) M.V. Lomonosov Moscow State University, Moscow, Russia 2) Center for Theoretical Problems of Physicochemical Pharmacology, RAS, Moscow, Russia
  • Artem A. Zhmurov 1) Moscow Institute of Physics and Technology, Dolgoprudny, Russia 2) Sechenov University, Moscow, Russia

DOI:

https://doi.org/10.14529/jsfi190104

Abstract

Even when modern computational platforms and parallel techniques are used, conventional all-atom simulations are limited both in terms of reachable timescale and number of atoms in the biomolecular system of interest. On the other hand, coarse-grained models, which allow to overcome this limitation, rely on proper and rigorous parametrization of the underlying force field. Here, we present a novel iterative approach for parametrization of coarse-grained models based on direct comparison of equilibrium simulations at all-atom and coarse-grained resolutions. In order to assess the accuracy of our method, we have built and parametrized an elastic network model (ENM) of the tubulin protolament consisting of four monomers. For this system, our method shows good convergence and the parametrized ENM reproduces protein dynamics in a finer way when compared to ENMs parametrized using the conventional approach. The presented method can be extended to other coarse-grained models with a slight adjustment of the equations describing the iterative scheme.

References

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Published

2019-04-23

How to Cite

Orekhov, P. S., Kirillov, I. V., Fedorov, V. A., Kovalenko, I. B., Gudimchuk, N. B., & Zhmurov, A. A. (2019). Parametrization of the Elastic Network Model Using High-Throughput Parallel Molecular Dynamics Simulations. Supercomputing Frontiers and Innovations, 6(1), 19–22. https://doi.org/10.14529/jsfi190104

Issue

Vol. 6 No. 1 (2019)

License

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-Non Commercial 3.0 License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.