Abstract
Owing to the increase of available computational capabilities and the potential for providing more accurate description, polarizable molecular dynamics force fields are gaining popularity in modelling biomolecular systems. It is, however, crucial to evaluate how much precision is truly gained with the increased cost and complexity of the simulation. Here, we leverage the NMRlipids open collaboration and Databank to assess the performance of available polarizable lipid models—the CHARMM-Drude and the AMOEBA-based parameters—against high-fidelity experimental data and compare them to the top-performing non-polarizable models. While some improvement in the description of ion binding to membranes is observed in the most recent CHARMM-Drude parameters, and the conformational dynamics of AMOEBA-based parameters are excellent, the best non-polarizable models tend to outperform their polarizable counterparts for each property we explored. The identified shortcomings range from inaccuracies in describing the conformational space of lipids to excessively slow conformational dynamics. Our results provide valuable insights for further refinement of polarizable lipid force fields and for selecting the best simulation parameters for specific applications.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Authors would like to point to the following changes to the previous versions of the manuscript. Following sentence is added to the Section 2.5 Analysis of Simulations: In this analysis, each lipid configuration is first aligned to the average structure from the trajectory, and principal component analysis is then applied to the heavy atom coordinates. The distribution convergence time of the motions along the first principal component,the motions with the longest convergence time, is then quantified and divided by the total trajectory length: teq = tconvergence/ts. A relative equilibration time teq > 1 indicates that individual lipids may not have sufficiently sampled their conformational ensembles and longer simulations are advisable. The following was added to Conclusions: This notion is further supported by the large relative equilibration times detected for the CHARMM-Drude models. Fig. 3 and SI Fig.3 are interchanged. A paragraph discussing the choice of water models is added to the Methods section.
