Recent developments in multiscale free energy simulations

Physics-based free energy simulations enable the rigorous calculation of properties, such as conformational equilibria, solvation or binding free energies. While historically most applications have occurred at the atomistic level of resolution, a range of advances in the past years make it possible now to reliably cross the temporal, spatial and theory scales for the modeling of complex systems or the efficient prediction of results at the accuracy level of expensive quantum-mechanical calculations. In this mini-review, we discuss recent methodological advances as well as opportunities opened up by the introduction of machine learning approaches, which tackle the diverse challenges across the different scales, improve the accuracy and feasibility, and push the boundaries of multiscale free energy simulations. •An array of rigorous simulation methods are available for calculating free energies.•Recent advances enable the crossing of temporal, spatial and theory scales.•Quantum mechanical/molecular mechanical methods and machine learning techniques can efficiently model the quantum mechanical potential energy surface.•Coarse-grained methods allow sampling of processes at larger time and spatial scales.