Physicochemical, Predicted ADME, and Structural Positioning of Azelaic Acid Within an Endocrine Oncology Reference Framework

Background: Azelaic acid, an established dermatologic dicarboxylic acid, was previously nominated as an unusual anticancer repurposing candidate. However, it remains unclear whether physicochemical properties, predicted ADME, or structural proximity to established endocrine anticancer drugs support this hypothesis. This study positioned azelaic acid relative to a clinically anchored endocrine anticancer reference panel using reference-defined space based on physicochemical and predicted ADME descriptors and two-dimensional structural similarity analyses. Methods: Sixteen clinically used endocrine anticancer drugs defined the reference set, with finasteride and dutasteride included as mechanistic comparators. SwissADME descriptors were screened for redundancy, standardized, and analyzed by principal component analysis and Euclidean nearest neighbor distances. Robustness was assessed by leave-one-reference-out, bootstrap, and WLOGP sensitivity analyses. Structural similarity was evaluated independently using Morgan fingerprints and Tanimoto coefficients. Results: The first two principal components explained 75.31% of reference variance. Flutamide was the nearest Clinical Reference to azelaic acid in physicochemical and predicted ADME space (d = 3.0063), but this distance exceeded the reference q90 threshold (2.6521), classifying azelaic acid as extrapolative. This classification persisted in all 16 leave-one-reference-out analyses and in 73.69% of 992 valid bootstrap replicates. Structurally, the highest reference similarity was observed with toremifene (T = 0.08696), below the minimum internal Clinical Reference nearest-neighbor similarity (0.13761); radius-3 sensitivity analysis preserved this result. Conclusions: Azelaic acid is neither a close structural analog nor a physicochemical and predicted ADME neighbor of established endocrine anticancer drugs. Its network-derived nomination therefore represents a non-canonical repurposing hypothesis requiring further experimental validation.