Parametrization of the elastic network model using high-throughput parallel molecular dynamics simulations

被引:1
|
作者
Orekhov, Philipp S. [1 ,2 ,3 ]
Kirillov, Ilya V. [1 ]
Fedorov, Vladimir A. [3 ]
Kovalenko, Ilya B. [3 ,4 ,5 ,6 ]
Gudimchuk, Nikita B. [3 ,7 ]
Zhmurov, Artem A. [1 ,2 ]
机构
[1] Moscow Institute of Physics and Technology, Dolgoprudny, Russia
[2] Sechenov University, Moscow, Russia
[3] M.V. Lomonosov Moscow State University, Moscow, Russia
[4] Federal Research and Clinical Center of Specialized Medical Care and Medical Technologies, Federal Medical and Biological Agency of Russia, Moscow, Russia
[5] Astrakhan State University, Astrakhan, Russia
[6] Scientific and Technological Center of Unique Instrumentation, RAS, Moscow, Russia
[7] Center for Theoretical Problems of Physicochemical Pharmacology, RAS, Moscow, Russia
来源
关键词
Atoms - Iterative methods - Coarse-grained modeling - Simulation platform;
D O I
10.14529/jsfi190104
中图分类号
学科分类号
摘要
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. © The Authors 2019.
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页码:19 / 22
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