Biophysics and Physicobiology
Online ISSN : 2189-4779
ISSN-L : 2189-4779
Regular Article
Building a macro-mixing dual‑basin Gō model using the Multistate Bennett Acceptance Ratio
Ai ShinobuChigusa KobayashiYasuhiro MatsunagaYuji Sugita
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Supplementary material

2019 Volume 16 Pages 310-321

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Abstract

The dual-basin Gō-model is a structural-based coarse-grained model for simulating a conformational transition between two known structures of a protein. Two parameters are required to produce a dual-basin potential mixed using two single-basin potentials, although the determination of mixing parameters is usually not straightforward. Here, we have developed an efficient scheme to determine the mixing parameters using the Multistate Bennett Acceptance Ratio (MBAR) method after short simulations with a set of parameters. In the scheme, MBAR allows us to predict observables at various unsimulated conditions, which are useful to improve the mixing parameters in the next round of iterative simulations. The number of iterations that are necessary for obtaining the converged mixing parameters are significantly reduced in the scheme. We applied the scheme to two proteins, the glutamine binding protein and the ribose binding protein, for showing the effectiveness in the parameter determination. After obtaining the converged parameters, both proteins show frequent conformational transitions between open and closed states, providing the theoretical basis to investigate structure-dynamics-function relationships of the proteins.

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© 2019 THE BIOPHYSICAL SOCIETY OF JAPAN
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