Abstract
The importance of physicochemical property calculation and measurement is well-established in drug discovery. In particular, lipophilicity predictions play a central role in target design and prioritization. While significant progress has been made in our ability to calculate both logP and logD, the quality of these predictions is limited by the size and diversity of the underlying data set. Access to diverse data sets and advanced models is often limited to large organizations or consortia, and they are not available to many students and practitioners of medicinal chemistry. A molecular matched pair analysis of median ΔlogD (7.4) contributions for substituents commonly used in drug discovery programs at Genentech is reported. The results of this ΔlogD analysis are compiled into a single table, which we anticipate will be of use to practicing medicinal chemists.