Parametrization of the Elastic Network Model Using High-Throughput Parallel Molecular Dynamics Simulations
Author(s) -
Philipp S. Orekhov,
Ilya V. Kirillov,
Vladimir A. Fedorov,
I. B. Kovalenko,
Nikita B. Gudimchuk,
Artem Zhmurov
Publication year - 2019
Publication title -
supercomputing frontiers and innovations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 16
eISSN - 2409-6008
pISSN - 2313-8734
DOI - 10.14529/jsfi190104
Subject(s) - parametrization (atmospheric modeling) , convergence (economics) , computer science , molecular dynamics , throughput , set (abstract data type) , force field (fiction) , statistical physics , algorithm , mathematical optimization , mathematics , physics , computational chemistry , chemistry , artificial intelligence , quantum mechanics , radiative transfer , economics , programming language , economic growth , telecommunications , wireless
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 protofilament 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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