Predictions where the HFE is off by 5 or more kcal/mol are more likely to obstruct rather than facilitate drug development pipelines. Moreover, consider again the hit discovery scenario where we alchemically decouple the ligand from the protein and from solvent and subtract one term from the other. In the case of a drug-like molecule, which can easily have a molecular weight of 400 or more, if we have an HFE error above 5 kcal/mol, the final ΔGbind estimate is likely to contain a large amount of error. In the hypothetical scenario where the decoupling-the-ligand-from-the-protein term is computed with perfect accuracy, the final ΔGbind estimate will contain the entirety of the error in the HFE calculations. Of course, protein force fields and the water models on which the decoupling-the-ligand-from-the-protein term depends are known to be imperfect. For example, commonly used force fields and water models tend to overstabilize proteins and underestimate their radii of gyration in the unfolded state ; the ff14SB and ff19SB protein force fields overestimate amino acid helical propensities with the TIP3P water model ; force fields also tend to overestimate the secondary structure content in simulations of intrinsically disordered proteins ; the osmotic pressure of guanidinium -acetate analog mixtures computed with CHARMM36 48 is significantly lower than the experimental value , indicating that the force field overestimates guanidinium -acetate interactions; overestimated cation -phosphate interactions overcondense DNA in simulations ; CHARMM27r underestimates the area per lipid, suggesting that the head groups attract one another too strongly ; authors have noted erroneous clustering of ions in simulations performed using standard force fields ; TIP3P grossly overestimates the self diffusion and isothermal compressibility of water, among other deficiencies, which OPC was developed to address . It has also been pointed out that carbohydrates are too selfattracting in CHARMM, AMBER, and OPLS , which in addition have flawed DNA base-stacking and ion -phosphate parameters which fail to reproduce the correct population ensembles in silico . This is by no means an exhaustive list of known force field deficiencies, many of which have been reviewed in more depth by Yoo and Aksimentiev who also suggest elegant modifications to the standard force fields to ameliorate some of these shortcomings . As evidenced by this work and many others, small molecule force fields are also far from perfect -common small molecule force fields can grossly mispredict HFEs, relative HFEs , and conformer energetics ; parameters between different force fields are often inconsistent i.e. force fields tend to underestimate the ligands' affinities for water (recall that the mode or center of the TIP3P error distribution is shifted from 0 to around -1 kcal/mol; see Fig. and). This tendency has been observed by other authors as well . In a thermodynamic cycle scenario, this is likely to result in an overestimation of the calculated ΔGbind, i.e. the calculated protein -ligand affinity will be greater than it is in reality. Disentangling the different sources of error is made all the more difficult given that existing force field inaccuracies are likely to drive sampling away from native conformational states and into spurious states which get sampled (at all or more often than they should) because of the flawed potential energy function underpinning the simulation. In addition, one can never definitively rule out the possibility that important conformational states have been missed , even if sampling has exceeded hundreds of microseconds, potentially milliseconds or more. In some cases, association or dissociation events can take up to several seconds making simulations impractical in determining rate and dissociation constants . Nevertheless, ABFE studies have been reported where errors tend to be within an acceptable range -usually between 1 and 3 kcal/ mol when examining small sets of ligands. With larger sets, however, errors can easily exceed 7 kcal/mol . Moreover, even this may be underestimating the difficulty of the problem.