In the ever-evolving landscape of energy materials, a groundbreaking study has emerged that could significantly impact the design and development of environmentally friendly alternatives. Researchers, led by Han Zhang from the Key Laboratory of Groundwater Resources and Environment at Jilin University in China, have developed a novel model to predict the binding affinities of liquid crystal monomers (LCMs) to nuclear hormone receptors (NHRs). This research, published in the journal “Safety of Ecotoxicology and Environmental,” sheds light on the molecular features influencing the potential endocrine-disrupting effects of LCMs, a critical concern for the energy sector.
Liquid crystal monomers are a class of materials widely used in various applications, including displays, sensors, and solar cells. However, their potential as endocrine disruptors has raised concerns about their environmental impact. “Understanding the molecular features that influence the binding affinities of LCMs to NHRs is crucial for designing safer and more sustainable materials,” said Han Zhang, the lead author of the study.
The study employed a multidimensional feature fusion model that integrates the automatic feature extraction capability of Message Passing Neural Network (MPNN) and the interpretability of Categorical Boosting (CatBoost). This approach allowed the researchers to predict the binding affinities of 1173 LCMs to 15 NHRs with enhanced accuracy. “By stratifying the activity cliffs into both training and test sets, we improved the model’s learning and generalization, providing a more robust prediction tool,” explained Zhang.
The findings revealed that the binding affinities of LCMs increased with the length of the carbon chain and the number of cyclohexyl and phenyl rings. The interpretability of the MPNN_CatBoost model further identified the total number of cyclohexyl and phenyl rings, polarity, and volume as common features influencing the binding affinities of LCMs with different NHRs. These insights offer a comprehensive understanding of the molecular features that contribute to the endocrine-disrupting effects of LCMs.
The implications of this research are far-reaching for the energy sector. As the demand for sustainable and environmentally friendly materials grows, the ability to predict and design materials with minimal endocrine-disrupting potential is invaluable. “This study provides a scientific foundation for the development of safer alternatives to LCMs, which can be integrated into various energy applications,” said Zhang.
The study’s innovative approach to feature fusion and activity cliffs analysis sets a new standard for predicting the binding affinities of chemical compounds. As the energy sector continues to evolve, the insights gained from this research will be instrumental in shaping the development of next-generation materials that are both high-performing and environmentally responsible.