Leveraging AlphaFold models to predict androgenic effects of endocrine-disrupting chemicals through zebrafish androgen receptor analysis
Creators: name: Karim, Md Adnan
name: Park, Chang Gyun
name: Cho, Hyunki
name: Sebastian, Annmariya Elayanithottathil
name: Ryu, Chang Seon
name: Yoon, Juyong
name: Kim, Young Jun
Publisher: name: Taylor & Francis
Year: 2025
Subjects: subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Physiology
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Cancer
subject: Inorganic Chemistry
subject: FOS: Chemical sciences
subject: Computational Biology

description: The androgen receptor (AR) activation by androgens is vital for tissue development, sexual differentiation, and reproductive attributes in zebrafish (<i>Danio rerio</i>). However, our understanding of the molecular mechanisms behind their activation remains limited. In this study, we employed both <i>ab initio</i> (AlphaFold) and homology (SWISS-MODEL) structure models of zebrafish androgen receptor ligand-binding domain (zAR-LBD) to explore the binding specificity, binding affinity, and molecular interactions of endogenous hormones (testosterone (T), 11-ketotestosterone (11-KT), and dihydrotestosterone (DHT)) in a computational simulation. Molecular docking analysis showed that both structures formed the same interactions and similar patterns of binding energy with androgens. Molecular Dynamics (MD) simulation analysis revealed that hydrogen bond occupancy aligned with <i>in vitro</i> findings related to androgenic effect. When comparing complexes modeled by SWISS-MODEL and AlphaFold, significant differences were observed in root mean square deviation (RMSD) and root mean square fluctuations (RMSF). The AlphaFold structures also exhibited a clear separation between ligands in principal component analysis. Further correlation analysis between in silico features and <i>in vitro</i> EC50 values identified MMPBSA energies as the most significant contributors to ligand-specific variance in the <i>in silico</i> complexes (<i>p</i> &lt; 0.05). Overall, this integrative approach offers significant insights into the molecular mechanisms underlying zebrafish AR activity. 3D structures of zAR-LBD were generated using <i>ab initio</i> prediction and homology modeling programs.The AlphaFold model demonstrated greater structural stability, which significantly impacted the accuracy, reliability, and reproducibility of data predictions compared to the SWISS-MODEL.Hydrogen bond patterns in the AlphaFold structure were consistent with <i>in vitro</i> androgenic effects.The integrated <i>in vitro</i> and <i>in silico</i> approaches holds potential as a complementary tool for screening androgenic EDCs. 3D structures of zAR-LBD were generated using <i>ab initio</i> prediction and homology modeling programs. The AlphaFold model demonstrated greater structural stability, which significantly impacted the accuracy, reliability, and reproducibility of data predictions compared to the SWISS-MODEL. Hydrogen bond patterns in the AlphaFold structure were consistent with <i>in vitro</i> androgenic effects. The integrated <i>in vitro</i> and <i>in silico</i> approaches holds potential as a complementary tool for screening androgenic EDCs.