Computational Insights on Xenobiotic Nuclear Receptor-Air Pollutant Interactions Through Molecular Docking and Dynamics Simulations

Abstract

Air pollution is a major global health risk, contributing to millions of deaths each year. Exposure to air pollutants can lead to a variety of adverse health effects, including oxidative stress, inflammation, and DNA damage. The nuclear receptor pregnane X receptor (PXR) is a xenobiotic sensor that plays a key role in the detoxification of environmental chemicals and air pollutants can activate these receptors, leading to the expression of genes involved in drug metabolism and detoxification. Elucidating the structural interactions of air pollutants with PXR provides insights into the mechanisms by which these pollutants exert their toxic effects. Using computational techniques, we screened 124 air pollutants toxic compounds from (APDB) against PXR and identified priority compounds for molecular dynamics simulation that revealed the dynamic binding mechanisms and structural conformations involved in PXR activation. Furthermore, the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses characterized the stability and flexibility of PXR-pollutant complexes. Together, these computational approaches provide unprecedented insights into the molecular basis of PXR activation by air pollutants. By enabling high-throughput screening and multi-faceted biophysical characterization of PXR interactions, this work elucidates the structural mechanisms linking air pollution to impaired xenobiotic metabolism. Integration of virtual screening, molecular dynamics, and rigorous biophysical analyses represents a powerful computational systems pharmacology pipeline for assessing health risks posed by ubiquitous environmental toxicants.