SBMs idealize the energy landscape based on two main ideas. First, natural proteins have evolved to avoid kinetic traps along the folding coordinate; this prevents the formation of long-lived folding intermediaries containing non-native interactions that could frustrate the folding reaction. Secondly, protein evolution has maximized the energy gap between the natively folded state and other competing configurations; these focused simplifications increase the number of protein molecules that populate the native basin and remove the excess of kinetic frustration. SBMs exploit these facts by focusing on the native structure geometry and contact information, exploring a conformational landscape entirely based on the native topology constraints. In this way, one can separate energetic from topological contributions, showing that essential features of protein folding are mainly encoded by the organization of the folded state. Following the same concept, SBM simulations have also been used to study protein-protein binding mechanisms or ligand-induced conformational changes. Additionally, multi-basin SBM potentials have served to study other complex mechanisms in protein dynamics, such as folding to competing native configurations, conformational shifts, domain swapping, knotting, or drastic structural rearrangements between functional and dysfunctional conformations. For a review on SBM applications, see reference , and for a review on the evolution of SBM models and their varied types of implementations for specific biophysical problems, see reference .