Accounting correctly, and computationally efficiently, for the entropic component of binding free energies remains a challenge for MMPBSA based computations. Here we investigated the use of the variational entropy technique on the ranking of different ESMACS protocols. In all cases the variational entropy was computed using the fluctuations from the 1traj simulations. As shown in Table the inclusion of this term results in a reduction in the performance of all protocols in simulations based on both initial models. Furthermore, the incorporation of explicit water molecules into the receptor reduces this to an even greater extent. Looking in more detail we see that some compounds suffer a deterioration in prediction whilst others manifest an improvement. For instance, Figure shows that the three DIV outliers 3, 4 and 5 are closer to the trend line whereas THQ12 and THQ13 are more poorly predicted. The entropic term is based on the variation in interaction energy during the complex simulation. As it compares versus the average it captures properties of the interaction energy surface. For molecules such as 6, 8, 9 and 10 that have few degrees of freedom, the interaction energy surface is likely to be steep, with small changes in conformation or translations leading to a rapid loss of interaction energy. Meanwhile, larger more flexible compounds such as 4 and 5 (which has a flexible benzhydryl core) can adapt to conformational changes of the receptor and maintain a favourable interaction energy, leading to a flatter potential surface. The results suggest that this entropic term is suited to the latter but not the former examples. Correctly capturing entropic contributions is key to obtaining truly reliable rankings in diverse datasets and further work in this area is required. Also, components of the MMPBSA calculation (particularly the surface area term) incorporate some entropic contributions and such double counting may account at least in part for the poor performance of variational entropy here.