Elucidation of endocrine−disrupting polychlorinated biphenyls binding potency with steroidogenic genes: Integration of in silico methods and ensemble docking approaches

A myriad of polychlorinated biphenyls (PCBs) may have potential to reproductive axis and endocrine disruptions. PCBs mostly breach the cholesterol biotransformation in mitochondria through interfering with steroidogenic genes and lead to adverse consequences in steroidogenesis; however, studies are scanty. In this examination, the combinations of quantitative structure-activity relationship (QSAR) modeling and ensemble docking approaches was performed to envisage structural properties of PCBs that influence the developmental toxicity, estrogen receptor−mediated impacts, and to provide a better comprehension of binding levels between PCBs, steroidogenic acute regulatory protein (StAR) and cholesterol side−chain cleavage enzyme (CYP11A1). Prognostic QSAR models were illustrated with good robustness and predictive ability. Models provide extensive data on applicability domain and similarities between PCBs and training set compounds was used to implement for clustering and classification of toxic PCBs by employing Self−Organizing Maps. Docking and interaction profiles interpretations provided various insights into the structural features of PCBs that influence the cholesterol binding to StAR and CYP11A1 domains. The non−polar, atomic π − stacking and halogen bonds of PCBs with novel hotspots residues of StAR and CYP11A1 was indicated subtle conformational changes that barrier to cholesterol binding and/or locks to cholesterol ejection from Ω1−loop of StAR, and inhibits cholesterol to pregnenolone biosynthesis by CYP11A1; thus, these are probably revealed as block−cluster mechanisms. These outcomes are potential to be useful to predict developmental toxicity, endocrine disruption potencies and anti-steroidogenic activities of other environmental pollutants and provided sorted pinpoints for further evaluation of interaction mechanisms of PCBs with other sterodogenic genes.