Non-bonded force field parameters from MBIS partitioning of the molecular electron density improve CB7 host-guest affinity predictions

Binding affinity prediction by means of computer simulation has been increasingly incorporated in drug discovery projects. Its wide application, however, is limited by the prediction accuracy of the free energy calculations. The main error sources are force fields used to describe molecular interactions and incomplete sampling of the configurational space. Organic host-guest systems have been used to address force field quality because they share similar interactions found in ligands and receptors, and their rigidity facilitates configurational sampling. Here, we test the binding free energy prediction accuracy for 14 guests with aromatic or adamantane core and the CB7 host using molecular electron density derived non-bonded force field parameters. We developed a computational workflow written in Python to derive atomic charges and Lennard-Jones parameters with the minimal basis iterative stockholder method using the polarized electron density of several configurations of each guest in the bound and unbound state. The resulting non-bonded force field parameters improve binding affinity prediction, especially for guests with adamantane core in which repulsive exchange and dispersion interactions to the host dominate.