Computational Analysis of Structure-Based Interactions for Novel H1-Antihistamines
AbstractAs 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. View Full-Text
- Supplementary File 1:
Supplementary (PDF, 832 KB)
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Yang, Y.; Li, Y.; Pan, Y.; Wang, J.; Lin, F.; Wang, C.; Zhang, S.; Yang, L. Computational Analysis of Structure-Based Interactions for Novel H1-Antihistamines. Int. J. Mol. Sci. 2016, 17, 129.
Yang Y, Li Y, Pan Y, Wang J, Lin F, Wang C, Zhang S, Yang L. Computational Analysis of Structure-Based Interactions for Novel H1-Antihistamines. International Journal of Molecular Sciences. 2016; 17(1):129.Chicago/Turabian Style
Yang, Yinfeng; Li, Yan; Pan, Yanqiu; Wang, Jinghui; Lin, Feng; Wang, Chao; Zhang, Shuwei; Yang, Ling. 2016. "Computational Analysis of Structure-Based Interactions for Novel H1-Antihistamines." Int. J. Mol. Sci. 17, no. 1: 129.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.