In this work, we report a novel method for the estimation of the hydration free energy of organic molecules, the structural descriptors correction (SDC) model. The method is based on a combination of the reference interaction site model (RISM) with several empirical corrections. The model requires only a small number of chemical descriptors associated with the main features of the chemical structure of solutes: excluded volume, branch, double bond, benzene ring, hydroxyl group, halogen atom, aldehyde group, ketone group, ether group, and phenol fragment. The optimum model was selected after testing of different RISM free energy expressions on a training set of 65 molecules. We show that the correction parameters of the SDC model are transferable between different chemical classes, which allows one to cover a wide range of organic solutes. The new model substantially increases the accuracy of calculated HFEs by RISM giving the standard deviation of the error for a test set of 120 organic molecules around 1.2 kcal/mol.
Molecular Density Functional Theory (MDFT) offers an efficient implicitsolvent method to estimate molecule solvation free-energies whereas conserving a fully molecular representation of the solvent. Even within a second order approximation for the free-energy functional, the so-called homogeneous reference fluid approximation, we show that the hydration free-energies computed for a dataset of 500 organic compounds are of similar quality as those obtained from molecular dynamics free-energy perturbation simulations, with a computer cost reduced by two to three orders of magnitude. This requires to introduce the proper partial volume correction to transform the results from the grand canonical to the isobaric-isotherm ensemble that is pertinent to experiments. We show that this correction can be extended to 3D-RISM calculations, giving a sound theoretical justification to empirical partial molar volume corrections that have been proposed recently.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.