Computational discovery of novel aryl hydrocarbon receptor modulators for psoriasis therapy.

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor involved in the regulation of many pathophysiological processes. Among these, immune system modulation, as well as regulation of skin homeostasis and inflammation, make it a promising target for psoriasis therapy. Tapinarof, an AhR agonist recently approved for psoriasis treatment, exerts its action through antioxidant, anti-inflammatory and barrier-restoring effects. In this study, we employed a computational drug-discovery approach to identify novel AhR modulators with psoriasis therapeutic potential. We performed a multi-step similarity-based screening in PubChem. Molecular docking led to the identification of diverse chemical scaffolds with high docking scores and potential AhR activity, some belonging to chemical classes with known pharmacological relevance. The stability of the binding geometries of the most promising compounds of each family was then verified through molecular dynamics simulations and pharmacokinetic characteristics were predicted using ADMETlab 2.0 and SwissADME. Notably, several identified compounds suggest a possible interplay between AhR signaling and sirtuin modulation, highlighting a previously unexplored avenue in psoriasis therapy. Our findings underscore the potential of computational approaches in accelerating the discovery of novel AhR-targeting agents and provide a foundation for further experimental validation.