TY - JOUR
T1 - Achieving Reproducibility and Replicability of Molecular Dynamics and Monte Carlo Simulations Using the Molecular Simulation Design Framework (MoSDeF)
AU - Craven, Nicholas C.
AU - Singh, Ramanish
AU - Quach, Co D.
AU - Gilmer, Justin B.
AU - Crawford, Brad
AU - Marin-Rimoldi, Eliseo
AU - Smith, Ryan
AU - DeFever, Ryan
AU - Dyukov, Maxim S.
AU - Fothergill, Jenny W.
AU - Jones, Chris
AU - Moore, Timothy C.
AU - Butler, Brandon L.
AU - Anderson, Joshua A.
AU - Iacovella, Christopher R.
AU - Jankowski, Eric
AU - Maginn, Edward J.
AU - Potoff, Jeffrey J.
AU - Glotzer, Sharon C.
AU - Cummings, Peter T.
AU - McCabe, Clare
AU - Siepmann, J. Ilja
N1 - Publisher Copyright:
© 2025 The Authors. Published by American Chemical Society.
PY - 2025/6/12
Y1 - 2025/6/12
N2 - Molecular simulations are increasingly used to predict thermophysical properties and explore molecular-level phenomena beyond modern imaging techniques. To make these tools accessible to nonexperts, several open-source molecular dynamics (MD) and Monte Carlo (MC) codes have been developed. However, using these tools is challenging, and concerns about the validity and reproducibility of the simulation data persist. In 2017, Schappals et al. reported a benchmarking study involving several research groups independently performing MD and MC simulations using different software to predict densities of alkanes using common molecular mechanics force fields [ J. Chem. Theory Comput. 2017, 4270−4280 ]. Although the predicted densities were reasonably close (mostly within 1%), the data often fell outside of the combined statistical uncertainties of the different simulations. Schappals et al. concluded that there are unavoidable errors inherent to molecular simulations once a certain degree of complexity of the system is reached. The Molecular Simulation Design Framework (MoSDeF) is a workflow package designed to achieve TRUE (Transparent, Reproducible, Usable-by-others, and Extensible) simulation studies by standardizing the implementation of molecular models for various simulation engines. This work demonstrates that using MoSDeF to initialize a simulation workflow results in consistent predictions of system density, even while increasing model complexity.
AB - Molecular simulations are increasingly used to predict thermophysical properties and explore molecular-level phenomena beyond modern imaging techniques. To make these tools accessible to nonexperts, several open-source molecular dynamics (MD) and Monte Carlo (MC) codes have been developed. However, using these tools is challenging, and concerns about the validity and reproducibility of the simulation data persist. In 2017, Schappals et al. reported a benchmarking study involving several research groups independently performing MD and MC simulations using different software to predict densities of alkanes using common molecular mechanics force fields [ J. Chem. Theory Comput. 2017, 4270−4280 ]. Although the predicted densities were reasonably close (mostly within 1%), the data often fell outside of the combined statistical uncertainties of the different simulations. Schappals et al. concluded that there are unavoidable errors inherent to molecular simulations once a certain degree of complexity of the system is reached. The Molecular Simulation Design Framework (MoSDeF) is a workflow package designed to achieve TRUE (Transparent, Reproducible, Usable-by-others, and Extensible) simulation studies by standardizing the implementation of molecular models for various simulation engines. This work demonstrates that using MoSDeF to initialize a simulation workflow results in consistent predictions of system density, even while increasing model complexity.
UR - http://www.scopus.com/inward/record.url?scp=105006743370&partnerID=8YFLogxK
U2 - 10.1021/acs.jced.5c00010
DO - 10.1021/acs.jced.5c00010
M3 - Review article
AN - SCOPUS:105006743370
SN - 0021-9568
VL - 70
SP - 2178
EP - 2199
JO - Journal of Chemical and Engineering Data
JF - Journal of Chemical and Engineering Data
IS - 6
ER -