  The parametrization of coarse-grained (CG) simulation models for molecular
systems often aims at reproducing static properties alone. The reduced
molecular friction of the CG representation usually results in faster, albeit
inconsistent, dynamics. In this work, we rely on Markov state models to
simultaneously characterize the static and kinetic properties of two CG peptide
force fields---one top-down and one bottom-up. Instead of a rigorous evolution
of CG dynamics (e.g., using a generalized Langevin equation), we attempt to
improve the description of kinetics by simply altering the existing CG models,
which employ standard Langevin dynamics. By varying masses and relevant
force-field parameters, we can improve the timescale separation of the slow
kinetic processes, achieve a more consistent ratio of mean-first-passage times
between metastable states, and refine the relative free-energies between these
states. Importantly, we show that the incorporation of kinetic information into
a structure-based parametrization improves the description of the helix-coil
transition sampled by a minimal CG model. While structure-based models
understabilize the helical state, kinetic constraints help identify CG models
that improve the ratio of forward/backward timescales by effectively hindering
the sampling of spurious conformational intermediate states.
