An automated analysis workflow for optimization of force-field parameters using neutron scattering data

•An automated workflow to optimize force-field parameters.•Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA.•The mechanism relies on molecular dynamics simulation and neutron scattering experimental data.•The workflow can be generalized to any other ex...

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Veröffentlicht in:Journal of computational physics 2017-07, Vol.340 (C), p.128-137
Hauptverfasser: Lynch, Vickie E., Borreguero, Jose M., Bhowmik, Debsindhu, Ganesh, Panchapakesan, Sumpter, Bobby G., Proffen, Thomas E., Goswami, Monojoy
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Sprache:eng
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Zusammenfassung:•An automated workflow to optimize force-field parameters.•Used the workflow to optimize force-field parameter for a system containing nanodiamond and tRNA.•The mechanism relies on molecular dynamics simulation and neutron scattering experimental data.•The workflow can be generalized to any other experimental and simulation techniques. Large-scale simulations and data analysis are often required to explain neutron scattering experiments to establish a connection between the fundamental physics at the nanoscale and data probed by neutrons. However, to perform simulations at experimental conditions it is critical to use correct force-field (FF) parameters which are unfortunately not available for most complex experimental systems. In this work, we have developed a workflow optimization technique to provide optimized FF parameters by comparing molecular dynamics (MD) to neutron scattering data. We describe the workflow in detail by using an example system consisting of tRNA and hydrophilic nanodiamonds in a deuterated water (D2O) environment. Quasi-elastic neutron scattering (QENS) data show a faster motion of the tRNA in the presence of nanodiamond than without the ND. To compare the QENS and MD results quantitatively, a proper choice of FF parameters is necessary. We use an efficient workflow to optimize the FF parameters between the hydrophilic nanodiamond and water by comparing to the QENS data. Our results show that we can obtain accurate FF parameters by using this technique. The workflow can be generalized to other types of neutron data for FF optimization, such as vibrational spectroscopy and spin echo.
ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2017.03.045