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

Vickie E. Lynch; Jose M. Borreguero; Debsindhu Bhowmik; Panchapakesan Ganesh; Bobby G. Sumpter; Thomas E. Proffen; Monojoy Goswami

doi:10.1016/j.jcp.2017.03.045

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

Vickie E. Lynch, Jose M. Borreguero, Debsindhu Bhowmik, Panchapakesan Ganesh, Bobby G. Sumpter, Thomas E. Proffen, Monojoy Goswami

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	128-137
Number of pages	10
Journal	Journal of Computational Physics
Volume	340
DOIs	https://doi.org/10.1016/j.jcp.2017.03.045
State	Published - Jul 1 2017

Funding

The development workflow was supported by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), Materials Sciences and Engineering Division. The use of Oak Ridge National Laboratory's (ORNL) SNS was sponsored by the Scientific User Facilities Division, Office of BES. We thank Gurpreet K. Dhindsa and Xiang-Qiang Chu from Wayne State University for providing us with the QENS data. The Pegasus workflow was funded by the DOE under contract number DE-SC0012636. This manuscript has been authored by ORNL, which is managed by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. DOE. This product includes software developed by and/or derived from the Globus project (http://www.globus.org/). This research used resources of the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Scientific User Facility supported by the Office of Science of the U.S. DOE under Contract No. DE-AC02-05CH11231. The original NAMD simulations were performed on TITAN at the Oak Ridge Leadership Computing Facility at the ORNL, which is supported by the Office of Science of the U.S. DOE under Contract No. DE-AC05-00OR22725. Part of this research was conducted at the Center for Nanophase Materials Sciences (CNMS), which is a DOE Office of Science User Facility.

Funders	Funder number
DOE Office of Scientific User Facility	DE-AC02-05CH11231
Office of BES
Scientific User Facilities Division
U.S. Department of Energy
Office of Science
Basic Energy Sciences
Oak Ridge National Laboratory
Wayne State University	DE-AC05-00OR22725, DE-SC0012636
Division of Materials Sciences and Engineering

Keywords

Biopolymers
CHARMM
Force-field optimization
Molecular dynamics
Neutron data analysis
Quasi-elastic neutron scattering

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10.1016/j.jcp.2017.03.045

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title = "An automated analysis workflow for optimization of force-field parameters using neutron scattering data",

abstract = "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.",

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author = "Lynch, {Vickie E.} and Borreguero, {Jose M.} and Debsindhu Bhowmik and Panchapakesan Ganesh and Sumpter, {Bobby G.} and Proffen, {Thomas E.} and Monojoy Goswami",

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AU - Borreguero, Jose M.

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AU - Ganesh, Panchapakesan

AU - Sumpter, Bobby G.

AU - Proffen, Thomas E.

AU - Goswami, Monojoy

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N2 - 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.

AB - 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.

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

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