SAMPL6 blind predictions of water-octanol partition coefficients using nonequilibrium alchemical approaches

In this paper, we compute, by means of a non equilibrium alchemical technique, the water-octanol partition coefcients (LogP) for a series of drug-like compounds in the context of the SAMPL6 challenge initiative. Our blind predictions are based on three of the most popular non-polarizable force felds, CGenFF, GAFF2, and OPLS-AA and are critically compared to other MD-based predictions produced using free energy perturbation or thermodynamic integration approaches with stratifcation. The proposed non-equilibrium method emerges has a reliable tool for LogP prediction, systematically being among the top performing submissions in all force feld classes for at least two among the various indicators such as the Pearson or the Kendall correlation coefcients or the mean unsigned error. Contrarily to the widespread equilibrium approaches, that yielded apparently very disparate results in the SAMPL6 challenge, all our independent prediction sets, irrespective of the adopted force feld and of the adopted estimate (unidirectional or bidirectional) are, mutually, from moderately to strongly correlated.