Revisión de los modelos computacionales que relacionan la estructura química con la disrupción del sistema endocrino

The endocrine disruptors are defined as a broad and diverse class of substances of natural or anthropogenic origin with the ability to interfere with some function of the endocrine system and, in doing so, cause adverse effects on an organism or its descendants. Endocrine disruption, associated with pathologies such as cancer, obesity, diabetes, and reproductive and immunological dysfunction, constitutes a specific form of toxicity whose regulation and legislation currently lack consensus. Computational methods, and within them chemoinformatic studies such as the prediction of quantitative structure-activity relationships (QSAR), are valuable research tools that have gradually occupied an important space in toxicological studies. This review proposes an analysis of the most recent state of the art related to QSAR modelling in the context of endocrine disruption. For this, case studies reported on three important hormonal mechanisms were selected, which represent synthesis, transport, and interaction with receptors. The summarized QSARs modelled the inhibitory capacity of the aromatase enzyme and the effects on the transthyretin transporter protein and the androgen receptor. These predictive tools can assist in prioritizing substances as potential endocrine disruptors and are therefore important contributions that guarantee the saving of time, material, and human resources.