Abstract—This investigation was performed to identify histamine H1-receptor antagonists from traditional Chinese medicine through virtual screening based on pharmacophore and molecular docking. First, the pharmacophore models were generated though ten known H1 receptor antagonists. The models were validated by a test database and shown to have good performance in external validation. The best pharmacophore was employed to screen Traditional Chinese Medicine Database, which resulting in a hit list of 421 compounds. Then, the hits were subjected to molecular docking for further refinement. An empirical scoring function was used to evaluate the affinity of the compounds and the target protein. Parts of compounds with high docking scores have been reported to have the related pharmacological activity in the literatures. The findings indicated that virtual screening based on pharmacophore and molecular docking can provide a helpful tool to reveal the active ingredients from Chinese herbs. It can be used for identification of novel H1 antagonists from Traditional Chinese Medicine.

Index Terms—Histamine H1-receptor, virtual screening, traditional chinese medicine, active natural ingredients identification.

X. Wang, Y. L. Zhang, Z. Z. Ren, and Y. J. Qiao are with the Beijing University of Chinese Medicine, Beijing 100102, China (e-mail: yjqiao@263.net).
Y. H. Xiang is with Capital Normal University, Beijing 100048, China. (e-mail: cnuxiangyh@163.com).

 

Cite:Xing Wang, Zhenzhen Ren, Yuhong Xiang, Yanling Zhang, and Yanjiang Qiao, "Pharmacophore Modelling, Molecular Docking and Virtual Screening for Histamine H1 Receptor Antagonists from Traditional Chinese Medicine," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 3, no. 5, pp. 438-443, 2013.