Recent methodological developments have also focused on selecting optimal collective variables for running metadynamics or other adaptive algorithms. This has for instance been achieved by reweighting techniques or machine learning approaches. As a recent example, it has been demonstrated that for a widely studied test system, benzamidine in trypsin, the water networks can be explicitly taken into account as part of collective variables, which leads to a much better agreement between simulations and experiments. Other methodological attempts focus on scaling the intermolecular interactions for different "umbrellas", thus reducing the potentially high barriers of the intermediate states while allowing to obtain the thermodynamic binding free energy. The aforementioned list of methodological developments in ABFE calculations is far from complete, and we refer the interested readers to recent reviews, in which the advances in the field are covered. Although various methods aiming at accurate calculations of ABFE have been introduced during the past decade, most of them are not yet implemented in popular software packages or have only been tested for toy models. Therefore, the US along simple reaction coordinates remains one of the most popular methods for computing ABFEs.