ArticlePharmaceutical research2023
N-oxidation Regioselectivity and Risk Prediction Using DFT-ALIE Calculations.
Article in Pharmaceutical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe 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.
objectiveThis study describes the development of an in-silico approach to identify N-oxide formation in APIs with respect to autoxidation.
methodsAverage 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.
resultsThe 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.
conclusionsThe 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.
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