There have been recent developments and extended applications of molecular dynamics (MD) to BFE. These, coupled with continued increases in computing power, bring more excitement and promise for the role of BFEs in CADD. Common approaches for predicting binding affinity, particularly BFEs, rely on MD simulations, and require the exploration of all relevant conformational space of a target and ligand of interest. Certain conformational dynamics of a biomolecule, such as a protein, could require simulations up to the millisecond timescales to capture such motions, and thus might not always be accessible. BFE simulations can also contain waters, ions, and sometimes cofactors, that make the system much larger and more challenging to achieve adequate sampling and convergence . In such cases, it would be difficult to assess if the inaccuracy in a computational method was due to limitations in the chosen energy model, limited sampling, or other factors such as protonation state of an ionizable residue. This can make BFE calculations on biomolecular systems less than ideal from the perspective of testing methods.