Prediction of the Interactions of a Large Number of Per- and Poly-Fluoroalkyl Substances with Ten Nuclear Receptors

• DOI: 10.1021/acs.est.3c05974
• Publication Date: 2024-02-29T21:14:45Z
• Authors: Ettayapuram Ramap...; Kathleen A. Durkin; Michele A. La Mer...; J. David Furlow; Jen-Chywan Wang; Martyn T. Smith
• Keywords: Fluorocarbons; Humans; Receptors, Cytoplasmic and Nuclear; Endocrine Disruptors

Per- and poly-fluoroalkyl substances (PFASs) are persistent, toxic chemicals that pose significant hazards to human health the environment. Screening large numbers of for their ability act as endocrine disruptors by modulating activity nuclear receptors (NRs) is challenging because time cost in vitro vivo experiments. For this reason, we need computational approaches screen these quickly prioritize them further testing. Here, utilized molecular modeling machine-learning predictions identify potential interactions between 4545 PFASs with ten different NRs. The results show some can bind strongly several receptors. Further, have very structures spread throughout chemical space. Biological validation silico findings should be a high priority.