Validation of molecular simulation: an overview of issues

Journal article

Computer simulation of molecular systems enables structure―energy―function relationships of molecular processes to be described at the sub-atomic, atomic, supraatomic or supra-molecular level and plays an increasingly important role in chemistry, biology and physics. To interpret results of such simulations appropriately, the quality of the calculated properties must be evaluated. This depends on (1) the degrees of freedom simulated, (2) the accuracy of the molecular model, interaction function or force field, (3) the equations of motion, integration scheme or other method used to sample degrees of freedom as well as the degree of sampling, (4) the boundary conditions, (5) the simulation software, and (6) how the software is used. When validating simulations against values of experimental observable quantities Qexp, one must also consider (1) the accuracy of Qexp, (2) the accuracy of the function Q(r N) used to calculate Q based on a molecular configuration r N of N particles,(3) the sensitivity of the function Q(r N)to the configuration r N, (4) the relative time scales of the simulation and experiment, (5) the degree to which the calculated and experimental properties are equivalent, and (6) the degree to which the system simulated matches the experimental conditions. Validation by comparison between experiment and simulation is seldom straightforward. Experimental data is limited in scope and generally corresponds to averages over both time and space. A critical analysis of the various factors that influence the apparent degree of (dis)agreement between simulations and experiment is presented and illustrated using examples from the literature. What can be done to enhance the validation of molecular simulation is also discussed.

Authors: van Gunsteren, W; Daura, X; Hansen, N; Mark, A; Oostenbrink, C

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Angewandte Chemie International Edition
• Volume: 130
• Issue: 4
• Pages: 894–915
• Publication date: 2017-12-27
• Acceptance date: 2017-06-20
• DOI: 10.1002/ange.201702945
• EISSN: 1521-3757
• ISSN: 0044-8249
• Keywords: causality; molecular dynamics simulation; correlation; experimental data; pseudo-validation; Monte Carlo simulation; errors