monitoring the unbinding of one ligand and the binding of another. However, the alchemical transitions offer a clear sampling advantage, thus reducing the computational cost of free energy calculations as well as a beneficial cancellation of errors arising from calculating the separate solvation and protein legs for similar ligands. The final result of the calculation is the relative affinity of the ligand to a protein with respect to the other ligand. The reader is referred to a recent review of alchemical methods and recommendations for their use. Due to tremendous algorithmic advances and continuous increase in computational power in the last decades, these calculations are nowadays frequently utilized. However, the calculations are still costly (≈ 10$ per relative free energy difference when using commercial software, while open source solutions can be cheaper 2 ). The accuracy with respect to experimental affinities is typically in the range of 1 -2 kcal mol -1 3-8 with best performing cases arguably capable of approaching experimental accuracy. When comparing to experiment, there are mainly four sources of error encountered in binding free energy calculations: system setup, force field parameters, sampling time and experimental uncertainty. Firstly, the set-up of the system has a significant impact on the prediction accuracy. This includes the exact chemical composition of the system, consisting of protein, ligand, solvent, potential ions and co-factors. All the molecules need to be in their correct tautomeric and charge state. Also, the initial coordinates of all atoms will strongly affect the results, as well as the simulation parameters mimicking the experimental conditions. Here, careful preparation and well-considered parameters keep this error contribution low, but this typically involves extensive manual work. The potential pitfalls and best practices to circumventing errors in system preparation were recently summarized. Furthermore, there are many approximations required to model such systems, which include the number of degrees of freedom treated, the treatment of finite-size effects, and especially the force field parameters used in classical mechanics simulations.