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

Philipp S. Orekhov; Ilya V. Kirillov; Vladimir A. Fedorov; Ilya B. Kovalenko; Nikita B. Gudimchuk; Artem A. Zhmurov

doi:10.14529/jsfi190104

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.

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