The success of residue-level CG force fields is underpinned by comprehensive comparison to experiments and advances in automatic parametrization Figure : Molecular dynamics simulations reveal drivers of biomolecular condensate formation. A) Atomistic molecular dynamics simulations can provide highly detailed and accurate descriptions of molecular interactions but at the expense of a high computational cost. To increase computational efficiency, particles can be grouped together to generate coarse-grained models. Some coarse-grained representations have an explicit solvent model. To increase computational efficiency further but retain some sequence-specificity, one can represent each amino acid as a single bead and employ an implicit water model. Adapted from Refs. and . . Building on Bayesian or maximum entropy frameworks, a large number of simulations are run and the results from these simulations are compared to experiments. To arrive at the CALVADOS models, Tesei et al. have taken a prior distribution for the hydrophobicity of amino acids from the literature. Simulations with the initial parameters were then compared to NMR and small angle X-ray scattering data. A few iterations yielded simulation parameters that can correctly rank the tendencies of proteins to phase separate . Including information from atomistic simulations to better describe how different pairs of amino acids interact may yield further improvements as shown, e.g., by Joseph et al. . Modifications to account for specific effects such as residue-pair specific interactions including cation-π interactions or for the simultaneous presence of folded and disordered regions can further increase the accuracy.