Endocrine activity prediction
Endocrine-disrupting chemicals threaten human and environmental health, making early identification essential.
Significant advances in computational methods have improved the prediction of potential endocrine-disrupting chemicals in recent years.
Endocrine activity prediction uses ligand based models, such as quantitative structure–activity relationship models, and structure-based methods based on protein–ligand interactions.
Advances in in silico approaches, such as consensus methods that combine the predictions of multiple individual models, hold promise for the largescale identification and prioritization of endocrine active chemicals.
https://www.cell.com/trends/endocrinology-metabolism/fulltext/S1043-2760(25)00221-8
