How environmental chemicals bind to hormone receptors: insights from computer simulations

What is it about?

Many everyday chemicals found in plastics, consumer products, and the environment can interfere with the human hormone system. These substances, known as endocrine-disrupting chemicals (EDCs), may affect health by binding to hormone receptors such as the estrogen and androgen receptors. Understanding how different chemicals interact with these receptors is essential for identifying potential risks and supporting regulatory decision-making. In this study, we used advanced computer-based methods to examine how a set of known and suspected EDCs bind to estrogen and androgen receptors at the molecular level. By simulating the interaction between chemicals and receptors, we were able to identify common binding patterns and key molecular features that influence receptor activation or inhibition. These simulations were combined with available experimental data to evaluate how well computational predictions reflect real biological behavior. The analysis was performed using automated workflows implemented in the KNIME analytics platform, allowing the systematic comparison of multiple chemicals and interaction types. We applied established computational techniques to estimate binding strength and to compare how structurally related chemicals differ in their interactions with hormone receptors. Our results show that computational methods can successfully capture trends observed in experimental assays and can reveal shared interaction mechanisms among different endocrine-disrupting chemicals. This work demonstrates how in silico tools can support the early screening and prioritization of chemicals for safety assessment, helping to reduce reliance on animal testing while improving our understanding of chemical–biological interactions relevant to human health.

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Photo by Bilal O. on Unsplash

Photo by Bilal O. on Unsplash

Why is it important?

Endocrine-disrupting chemicals represent a growing concern for human health and environmental safety, yet experimental testing of large numbers of chemicals is time-consuming, costly, and often limited by ethical constraints. This work addresses this challenge by demonstrating how reliable computer-based methods can be used to investigate how diverse chemicals interact with key hormone receptors at the molecular level. The study is important because it goes beyond predicting whether a chemical binds to a receptor and instead focuses on identifying common binding patterns and interaction mechanisms. By combining molecular simulations with automated data analysis workflows, the approach enables systematic comparison across multiple compounds and receptors. This provides mechanistic insight that is difficult to obtain from experimental assays alone. Importantly, the work shows that well-established computational techniques, when applied within standardized and reproducible workflows, can support chemical prioritization and risk assessment. This is particularly relevant in the context of current regulatory efforts to reduce animal testing and to adopt new approach methodologies for chemical safety evaluation. The framework presented here can be readily extended to other receptor systems and chemical classes, contributing to more efficient and transparent safety assessment strategies.

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