More detailed CG simulation approaches can provide more chemical specificity, but at the expense of increased computational demands (Fig. ). Recently, hybrid atomistic/CG force fields that can capture the formation of secondary structure in the context of protein phase separation have been developed . The presence of secondary structure elements can mediate phase separation . Furthermore, the general purpose Martini3 CG model , which has been developed for simulating many different kinds of (bio)molecules can also be used to simulate disordered proteins and their phase behavior . Because in this model amino acids are represented by several beads, one might be able to infer information about the roles of preferential side chain interactions in driving phase separation. For example, Martini3 simulations highlighted Arg and Lys residues to be important for the recruitment of the client protein MUT-8 to MUT-16 condensates . CG simulations also highlighted Arg-Tyr interactions between the condensate and the client. Atomistic MD simulations and binding experiments showed that the Arg residues are indeed essential for the recruitment of the client, but that the Martini3 simulations overestimate the Lys interactions with aromatic residues . The Martini3 model has been used to study the effect of changes in salt concentrations on condensation , and rescaled Martini3 can capture the relative phase separation propensities of disordered proteins in accordance with experiments . Recently, Martini3 was extended to simulate chemical reactions in condensates, i.e., the reshuffling of covalent bonds . One challenge with the Martini model is that proteinwater and/or protein-protein interactions need to be rebalanced for simulations of proteins with disordered regions and their condensates . It is an open question how well sequence-specific interactions in condensates are captured in this context and whether the rescaling affects the balance of different intermolecular interactions.