Structure-Based Virtual Screening of Perfluoroalkyl and Polyfluoroalkyl Substances (PFASs) as Endocrine Disruptors of Androgen Receptor Activity Using Molecular Docking and Machine Learning
Abstract:Perfluoroalkyl and
Polyfluoroalkyl Substances (PFASs) pose
a substantial threat as endocrine disruptors, and thus early identification of
those that may interact with steroid hormone receptors, such as the androgen
receptor (AR), is critical. In this study we screened 5,206 PFASs from the
CompTox database against the different binding sites on the AR using both molecular
docking and machine learning techniques. We developed support vector machine
models trained on Tox21 data to classify the active and inactive… Show more
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