This requires new instances of PyRosetta for different types of parameters. cg_pyrosetta initializes PyRosetta using the flags shown in table 2 to create new instances of PyRosetta with different parameter files. cg_pyrosetta can be installed using PyRosetta/Rosetta v2021.45dev61799 or versions after this. The CG movers added to cg_pyrosetta all inherit from the Rosetta mover base class, but are implemented in Python. Rosetta's default torsion movers (small and shear movers) are implemented to change protein φ and ψ angles and are therefore incompatible with the CG models we added to cg_pyrosetta. In the CG model space, we are interested in searching over all available degrees of freedom. We therefore developed a CG torsion mover, a CG bond-angle mover and CG bond-length movers for sampling all degrees of freedom in these CG models. When used on a CG model these movers find all the available degrees of freedom of their respective type and randomly perturb one of them. Combining these new CG movers and Rosetta's exisiting MonteCarlo and Minimizer objects we develop a folding algorithm which can quickly explore large regions of configuration space and identify minimum energy structures of our first-generation CG models. Further details on the folding algorithm developed are discussed in section 2.3