The software provides two execution modes, which conform to two different CG modeling philosophies. Using execution mode 1, all equilibrium values (𝑙 0𝑖 , 𝜃 0𝑗 and 𝜙 0𝑘 in Eq. 1) are optimized together with the force constants (𝑘 𝑏𝑖 , 𝑘 𝑎𝑗 and 𝑘 𝑑𝑘 in Eq. 1), for each group of bonds, angles and dihedrals. This procedure, based on the BI philosophy, allows for a fully automatic and relatively easy usage of the software, which precisely reproduces geoms distributions from an AA-mapped reference trajectory. However, using Swarm-CG in execution mode 1 as a black box may also have undesired effects. For instance, an insufficient conformational sampling in the reference AA-MD trajectory may automatically introduce artifacts in the optimized CG model. Indeed, poor sampling can attribute excessive statistical weight to some molecular conformation, which will affect the resulting CG model and limit its accuracy. For example, the folding of flexible hydrophobic molecules in polar solvents into metastable compact conformations may be typically oversampled in AA-MD simulations. While the folding is a consequence of solvophobic interactions, it may result in a CG model in which the output BP encode the bending of straight linear chains (e.g. long alkyl groups, formed by a straight chain of CG beads) in the form of spurious angles equilibrium values (different from e.g. 180°), producing shorter bonds, etc. Similarly, limited sampling can affect the modeling of symmetric molecules (e.g. the branched molecules of Figure ), by enforcing non-symmetric parameters that emerge by oversampled local minima, in contradiction with the chemical structure of the molecule. In such cases, this may eventually result into having an "effect" emerging from the AA models and encoded into the bonded parameters of the CG models, which may then affect the way molecules interact between them, their flexibility, transferability across different molecular environments, etc. However, Swarm-CG is well equipped to mitigate such spurious effects of limited MD sampling, by averaging in the AA-mapped reference the distributions obtained for structurally symmetric/identical parts of the molecule. It is also worth underlining that such possible issues emerging from using a not properly sampled AA-MD trajectory as the reference is not specific of Swarm-CG, but rather a general drawback of the BI approach. Therefore, while BI is standard and widely used, one should always be careful and check that the AA-MD trajectory is sufficiently well-sampled to ensure that the observed properties of the optimized CG models are reliable. While enhanced sampling approaches such as Replica Exchange Molecular Dynamics (REMD) and metadynamics may be useful in this sense, said issues can be mitigated by using the second execution mode (mode 2) of Swarm-CG. Execution mode 2 is identical to mode 1, with the exception that equilibrium values for angles and dihedrals can be pre-defined in the preliminary CG model and conserved during the optimization, while only their force constants are optimized (along with all bonds parameters). For example, in the case of flexible molecules containing long solvophobic chains (e.g. alkyl chains in water), execution mode 2 allows to manually pre-define chemically-relevant equilibrium angles values between the alkyl CG beads (e.g. 180°) and to obtain an accurate folding propensity of the molecule (i.e. the correct folding effect) exclusively by softening angles force constants, without biasing the equilibrium conformation (and without encoding such bias in the optimized CG models). Compared to mode 1, mode 2 requires more experience of the user and some knowledge of the molecular system, as well as an initial hands-on setup.