A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d6 Fe(II) Complexes

Handley, Christopher M.; Deeth, Robert J.

Abstract

The next generation of force fields (FFs), regardless of the accuracy of the potential energy representation, will always
have parameters that must be fitted in order to reproduce experimental and/or ab initio data accurately. Single objective methods
have been used for many years to automate the obtaining of parameters, but this leads to ambiguity. The solution depends on the
chosen weights and is therefore not unique. There have been few advances in solving this problem, which thus remains a major
hurdle for the development of empirical FF methods. We propose a solution based on multi-objective evolutionary algorithms
(MOEAs). MOEAs allow the FF to be tuned against the desired objectives and offer a powerful, efficient, and automated means to
reparameterize FFs, or even discover the parameters for a new potential. Here, we illustrate the application of MOEAs by
reparameterizing the ligand field molecular mechanics (LFMM) FF recently reported for modeling spin crossover in iron-
(II)
amine complexes (Deeth et al. J. Am. Chem. Soc. 2010, 132, 6876). We quickly recover the performance of the original
parameter set and then significantly improve it to reproduce the geometries and spin state energy differences of an extended series of
complexes with RMSD errors in Fe
N and N
N distances reduced from 0.06 Å to 0.03 Å and spin state energy difference RMSDs
reduced from 1.5 kcal mol
1 to 0.2 kcal mol
1
. The new parameter sets highlight, and help resolve, shortcomings both in the nonLFMM FF parameters and in the interpretation of experimental data for several other Fe(II)N6 amine complexes not used in the
FF optimization.

Citation

Handley, C. M., & Deeth, R. J. (2012). A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d6 Fe(II) Complexes. Journal of Chemical Theory and Computation, 8(1), 194-202. https://doi.org/10.1021/ct200584a

• Journal Article Type: Article
• Online Publication Date: Dec 14, 2011
• Publication Date: Jan 10, 2012
• Deposit Date: Aug 13, 2020
• Journal: Journal of Chemical Theory and Computation
• Print ISSN: 1549-9618
• Electronic ISSN: 1549-9626
• Publisher: American Chemical Society
• Peer Reviewed: Peer Reviewed
• Volume: 8
• Issue: 1
• Pages: 194-202
• DOI: https://doi.org/10.1021/ct200584a
• Public URL: https://nottingham-repository.worktribe.com/output/4830505
• Publisher URL: https://pubs.acs.org/doi/10.1021/ct200584a