Opportunities for Tapping into Three-Dimensional Chemical Space through a Quaternary Carbon

The medicinal chemistry community has become increasingly aware of the value of tracking calculated physical properties such as molecular weight, topological polar surface area, rotatable bonds, and hydrogen bond donors and acceptors. We hypothesized that the shift to high-throughput synthetic practices over the past decade may be another factor that may predispose molecules to fail by steering discovery efforts toward achiral, aromatic compounds. We have proposed two simple and interpretable measures of the complexity of molecules prepared as potential drug candidates. The first is carbon bond saturation as defined by fraction sp(3) (Fsp(3)) where Fsp(3) = (number of sp(3) hybridized carbons/total carbon count). The second is simply whether a chiral carbon exists in the molecule. We demonstrate that both complexity (as measured by Fsp(3)) and the presence of chiral centers correlate with success as compounds transition from discovery, through clinical testing, to drugs. In an attempt to explain these observations, we further demonstrate that saturation correlates with solubility, an experimental physical property important to success in the drug discovery setting.

An analysis of chemical reactions used in current medicinal chemistry (2014), three decades ago (1984), and in natural product total synthesis has been conducted. The analysis revealed that of the current most frequently used synthetic reactions, none were discovered within the past 20 years and only two in the 1980s and 1990s (Suzuki-Miyaura and Buchwald-Hartwig). This suggests an inherent high bar of impact for new synthetic reactions in drug discovery. The most frequently used reactions were amide bond formation, Suzuki-Miyaura coupling, and SNAr reactions, most likely due to commercial availability of reagents, high chemoselectivity, and a pressure on delivery. We show that these practices result in overpopulation of certain types of molecular shapes to the exclusion of others using simple PMI plots. We hope that these results will help catalyze improvements in integration of new synthetic methodologies as well as new library design.