N-oxidation Regioselectivity and Risk Prediction Using DFT-ALIE Calculations

The formation of N-oxide degradants is a major concern in development of new drugs due to potential effects on a compound's pharmacological activity. Such effects include but are not limited to solubility, stability, toxicity, and efficacy. In addition, these chemical transformations can impact physicochemical properties that affect drug manufacturability. Hence identification and control of N-oxide transformations is of critical importance in the development of new therapeutics.

This study describes the development of an in-silico approach to identify N-oxide formation in APIs with respect to autoxidation.

Average Local Ionization Energy (ALIE) calculations were carried out using molecular modeling techniques and application of Density Functional Theory (DFT) at the B3LYP/6-31G(d,p) level of theory. A total of 257 nitrogen atoms and 15 different oxidizable nitrogen types were used in developing this method.

The results show that ALIE could be reliably used to predict the most susceptible nitrogen for N-oxide formation. A risk scale was developed that rapidly categorizes nitrogen's oxidative vulnerabilities as small, medium, or high.

The developed process presents a powerful tool to identify structural susceptibilities for N-oxidation as well as enabling rapid structure elucidation in resolving potential experimental ambiguities.