High-throughput Virtual Screen of Endocrine-disrupting Chemicals Identifies Disruptors of EGFR Signaling
Jesikeiwicz, L.; Marathe, R.; Sepehri, B.; Demissie, R.; Lee, H.; Veiga-Lopez, A.; Villegas, J. A.
Show abstract
Chemical exposures during pregnancy are linked to an increased risk of pregnancy complications that contribute significantly to maternal and infant morbidity and mortality and can lead to long term health consequences for both the mother and the offspring. The placenta, a central regulator of pregnancy health, is a direct target of environmental toxicants. Epidermal growth factor receptor (EGFR), highly expressed in the placenta, regulates proliferation, migration, invasion, fusion, and cellular bioenergetics. To identify compounds of environmental concern with potential for EGFR-disrupting activity, we optimized a high-throughput virtual screening protocol for the identification of EGFR inhibitors and achieved enrichment factors of EF1% = 10.09, EF5% = 3.86, and EF10% = 3.0 in a benchmarking dataset. We applied this protocol to screen the Collaborative Estrogen Receptor Activity Prediction Project database, finding that top-scoring compounds were enriched for aromatic and fused-ring chemical classes, including dyes. Kinase activity assays revealed that two out of thirteen selected compounds, Vat Red 32 and Reactive Red 136, inhibited EGFR kinase activity with micromolar IC50 values. Additionally, pose refinement with molecular dynamics simulations characterized the binding interactions of Reactive Red 136 within the EGFR kinase domain, and functional assays in HTR-8/SVneo placental trophoblast cells showed that Reactive Red 136, but not Vat Red 32, partially attenuated EGF-mediated cell migration despite both compounds inhibiting EGFR kinase activity. Together, this study has generated an enriched dataset of candidate environmental EGFR modulators, with experimental validation confirming enrichment for EGFR-disrupting activity among the selected compounds. These results provide a valuable resource for toxicological studies.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- NeurotoxKb: compilation, curation and exploration of a knowledgebase of environmental neurotoxicants specific to mammals 96%
- Low concentrations of ethylene bisdithiocarbamate pesticides maneb and mancozeb impair manganese and zinc homeostasis to induce oxidative stress and caspase-dependent apoptosis in human hepatocytes 95%
- ExHuMId: A curated resource and analysis of Exposome of Human Milk across India 95%
Similar papers in this journal
Similar papers in this journal
- Proteome-wide reverse molecular docking reveals folic acid receptor as a mediator of PFAS-induced neurodevelopmental toxicity 96%
- Machine Learning-based Biomarkers Identification and Validation from Toxicogenomics - Bridging to Regulatory Relevant Phenotypic Endpoints 95%
- Toxicity of 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NKK) in early development: a wide-scope metabolomics assay in zebrafish embryos 93%
Similar papers in this journal
- Cell Painting and chemical structure read-across can complement each other for rat acute oral toxicity prediction in chemical early de-risking 93%
- Cannabidiol Toxicity Driven by Hydroxyquinone Formation 92%
- Formaldehyde Exposure Induces Systemic Epigenetic Alterations in Histone Methylation and Acetylation 92%
Similar papers in this journal
- Endocrine disrupting chemicals and COVID-19 relationships: a computational systems biology approach 95%
- Potential Systemic Availability Classification of Chemicals for Safety Assessment 95%
- Network-based investigation of petroleum hydrocarbons-induced ecotoxicological effects and their risk assessment 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.