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Updated: Mar 26, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Computational Analysis of Structure-Based Interactions for Novel H₁-Antihistamines
Yinfeng Yang1, Yan Li2, Yanqiu Pan3
1Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Department of Materials Sciences and Chemical Engineering, Dalian University of Technology, Dalian 116024, China. yinfengyang@yeah.net.
Abstract:
As a chronic disorder, insomnia affects approximately 10% of the population at some time during their lives, and its treatment is often challenging. Since the antagonists of the H₁ receptor, a protein prevalent in human central nervous system, have been proven as effective therapeutic agents for treating insomnia, the H₁ receptor is quite possibly a promising target for developing potent anti-insomnia drugs. For the purpose of understanding the structural actors affecting the antagonism potency, presently a theoretical research of molecular interactions between 129 molecules and the H₁ receptor is performed through three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques. The ligand-based comparative molecular similarity indices analysis (CoMSIA) model (Q² = 0.525, R²ncv = 0.891, R²pred = 0.807) has good quality for predicting the bioactivities of new chemicals. The cross-validated result suggests that the developed models have excellent internal and external predictability and consistency. The obtained contour maps were appraised for affinity trends for the investigated compounds, which provides significantly useful information in the rational drug design of novel anti-insomnia agents. Molecular docking was also performed to investigate the mode of interaction between the ligand and the active site of the receptor. Furthermore, as a supplementary tool to study the docking conformation of the antagonists in the H₁ receptor binding pocket, molecular dynamics simulation was also applied, providing insights into the changes in the structure. All of the models and the derived information would, we hope, be of help for developing novel potent histamine H₁ receptor antagonists, as well as exploring the H₁-antihistamines interaction mechanism.
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