Since we have a good benchmark of AA and CG models for (relatively) small and flexible molecules that generate supramolecular polymers in different environments, we started from here in showing the potential of Swarm-CG. We chose the examples reported in Figure . These are relatively flexible molecules that generate supramolecular structures in water (e.g. BTA and BTT) or in organic solvents (e.g. BTA, Porphyrin, NDI-based units). These molecules show an intrinsic symmetric character, having three (BTA and BTT), two (NDI) or four (Porphyrin) structurally identical arms originating from the molecule center. Thus, these are the typical motifs which, in a blind BI approach, may suffer of a spurious different parametrization of identical groups given by insufficient sampling. In this sense, they represent the ideal ground to test Swarm-CG. For these systems, we compared the results obtained using Swarm-CG execution modes 1 vs. mode 2. As previously mentioned (cf. section 2.4), execution mode 2 allows the user to pre-set conserved equilibrium values for angles and dihedrals, while Swarm-CG then optimizes the corresponding force constants to have the CG model behaving consistently with the reference AA model. For the CG modeling of BTA, BTT, NDI and porphyrin-based motifs, we relied on previously developed AA and CG models, where intramolecular non-bonded interactions were accurately tuned using state-of-theart enhanced sampling techniques. Considering the non-bonded parameters of these CG models as reliable, we used Swarm-CG exclusively to optimize their bonded terms.