Quantum Chemical GA-MLR, Cluster Model, and Conceptual DFT Descriptors Studies on the Binding Interaction of Estrogen Receptor Alpha with Endocrine Disrupting Chemicals
Source abstract
Abstract
In the present study, the predication of the binding affinity (log RBA) of estrogen receptor alpha with three categories of environmental endocrine disrupting chemicals (EDCs), namely, PCB, phenol, and DDT, is performed by the quantum chemical genetic algorithm multiple linear regression (GA-MLR) method. The result of the optimal model indicates that log RBA increases with increasing the electrophilicity and hydrophobicity of EDCs. However, by using the quantum chemical cluster model approach, the modeling results reveal that electrostatic interaction and hydrogen bonding play a significant role. The chemical reactivity descriptors calculated based on the conceptual density functional theory also indicate that the binding mechanism of charge-controlled interaction is superior to that of frontier-controlled interaction.
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Research context
OpenAlex topics: Computational Drug Discovery Methods · Free Radicals and Antioxidants · Estrogen and related hormone effects
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Air Pollution and Environmental Material Lab, Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 10617, Taiwan
Environmental Molecular and Electromagnetic Physics (EMEP) Laboratory, Department of Soil and Environmental Sciences, National Chung Hsing University, Taichung 40227, Taiwan
Funding
National Science Council of Taiwan, Republic of China
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