Qualitative and quantitative simulation of androgen receptor antagonists: A case study of polybrominated diphenyl ethers

Abstract

Recently, great attention has been paid to the identification and prediction of the androgen disrupting potencies of polybrominated diphenyl ethers (PBDEs). However, few existing models can discriminate active and inactive compounds, which make the quantitative prediction process including the quantitative structure-activity relationship (QSAR) technique unreliable. In this study, different grouping methods were investigated and compared for qualitative identification, including molecular docking and molecular dynamics simulations (MD). The results showed that qualitative identification based on MD, which is lab-independent, accurate and closer to the real transcriptional activation process, could separate 90.5% of active and inactive chemicals and was preferred. The 3D-QSAR models built as the quantitative simulation method showed r2 and q2 values of 0.513 and 0.980, respectively. Together, a novel workflow combining qualitative identification and quantitative simulations was generated with processes including activeness discrimination and activity prediction. This workflow, for analyzing the antagonism of androgen receptor (AR) of PBDEs is not only allowing researchers to reduce their intense laboratory experiments but also assisting them in inspecting and adjusting their laboratory systems and results.