In Silico and In Vitro multiple analysis approach for screening naturally derived ligands for red seabream aryl...

Area of Science:

• Environmental Toxicology
• Molecular Pharmacology
• Marine Biology

Background:

• The aryl hydrocarbon receptor (AHR) is a transcription factor mediating toxic compound effects, with natural ligands like flavonoids showing regulatory roles in inflammation and anti-cancer processes.
• Natural AHR ligands accumulate in wildlife, particularly fish, but their diverse structures and specific AHR responses in marine fish remain understudied.
• Developing novel screening methods is essential to assess various natural AHR ligands in marine fish, considering species-specific AHR characteristics.

Purpose of the Study:

• To develop a predictive model for screening potential natural ligands that activate red seabream AHR1 and AHR2 (rsAHR1 and rsAHR2).
• To investigate the transcriptional activity and isoform specificity of various natural AHR ligands in marine fish using red seabream as a model.
• To establish a robust screening approach by integrating in silico and in vitro data with large toxicological databases.

Main Methods:

• Constructed in vitro reporter gene assays for rsAHR1 and rsAHR2 in COS-7 cells to measure the transcriptional activity of 10 natural AHR ligands.
• Developed in silico homology models of rsAHR1 and rsAHR2 ligand-binding domains (LBDs) to calculate docking energies (U_dock) for natural ligands and dioxins.
• Validated the predictive model using Tox21 big data, analyzing docking energies against human AHR activity for a large chemical library.

Main Results:

• FICZ, Genistein, Daidzein, I3C, DIM, Quercetin, and Baicalin induced rsAHR1 and rsAHR2 transcriptional activity, with distinct isoform-specific responses observed for I3C, Baicalin, DIM, and Quercetin.
• A significant correlation was found between in silico docking energies and in vitro transcriptional activity (EC50) for rsAHR1 (R²=0.74) and rsAHR2 (R²=0.83), validating the homology models.
• The in silico model effectively distinguished between active and inactive compounds using U_dock values and showed correlation with human AHR activity from the Tox21 database (R²=0.45).

Conclusions:

• The study successfully developed and validated an in silico model for screening natural AHR ligands in marine fish, specifically red seabream.
• The developed model provides equations to quantitatively estimate AHR transactivation, serving as a valuable tool for assessing environmental exposure risks in marine ecosystems.
• This integrated in silico/in vitro approach offers a novel, efficient method for identifying potential AHR agonists and understanding their toxicological implications in marine fish.