Representation of the Conformational Ensemble of Peptides in Coarse Grained Simulations

Proteins/peptides can adopt to different environments by altering their conformation. Novel experimental techniques have enabled a quantitative characterization of this structural heterogeneity. In molecular dynamics simulations capturing this conformational ensemble quantitatively remains a major challenge. Even in atomistic simulations one has to find the best force field for the molecule of interest. With coarse grained (CG) simulations, where the aim is to reduce the degrees of freedom to reach the relevant length and time scales, representation of the conformational ensemble becomes even more problematic. Here, we revisit a recent CG model from our group, which was designed and tested for representing the aggregation driven conformational change of LKα14 peptide. We demonstrate here, that the structure/physics based approach used in the original parameterization of our CG model, strongly depends on the reference system chosen and excluded volume interactions. The updated model can recover the whole conformational ensemble in a quantitative manner, while maintaining the aggregation driven conformational transformation feature. This balanced parametrization leads to a sequence transferable CG model.