Molecular dynamics (MD) simulations are an important tool for the theoretical study of soft matter systems and have been successfully used to model a large variety of systems such as polymers, liquid crystals, amphiphiles, and proteins . When used in combination with experiments, MD simulations help to gain a deeper understanding of complex phenomena by giving access to structural, mechanical and dynamical properties . The all-atom (AA) description of soft matter systems is fairly accurate, but suffers from spatio-temporal limitations. For instance, it remains challenging, if not impossible, to model the characteristic long time scales of certain polymer processes, such as the glass-transition, the dynamics of long chains, or the phase segregation of block copolymers . Coarse-grained (CG) simulations offer a good compromise between computational efficiency and accuracy. Generic CG (G-CG) models describe polymer-like macromolecules as beads connected by elastic springs, where each bead represents a group of atoms or monomers, and possibly other interaction potentials. The efficiency of CG simulations comes from a reduced number of degrees of freedom, simpler potential functions, longer simulation time-steps, and the possibility of using an implicit solvent. Despite being comparatively simpler than AA models, G-CG models have been successfully applied to a wide range of polymeric systems, including solutions and melts of neutral polymer chains , weak (pH-responsive) polypeptides , polyelectrolyte nanogels and biomolecules such as DNA and proteins , often yielding quantitative or semi-quantitative agreement with AA simulations and experimental results.