Study on lipid-lowering traditional Chinese medicines based on pharmacophore technology and patent retrieval.
- Author:
Xiao-qian HUO
;
Yu-su HE
;
Lian-sheng QIAO
;
Zhi-yi SUN
;
Yan-ling ZHANG
- Publication Type:Journal Article
- MeSH:
Acyl Coenzyme A;
metabolism;
Animals;
Databases, Factual;
Drugs, Chinese Herbal;
chemistry;
pharmacology;
Hydrophobic and Hydrophilic Interactions;
Hydroxymethylglutaryl-CoA Reductase Inhibitors;
chemistry;
pharmacology;
Lipid Metabolism;
drug effects;
Lipids;
blood;
Medicine, Chinese Traditional;
Models, Molecular;
Quantitative Structure-Activity Relationship;
Technology
- From:
China Journal of Chinese Materia Medica
2014;39(24):4839-4843
- CountryChina
- Language:Chinese
-
Abstract:
The combined application of statins that inhibit HMG-CoA reductase and fibrates that activate PPAR-α can produce a better lipid-lowering effect than the simple application, but with stronger adverse reactions at the same time. In the treatment of hyperlipidemia, the combined administration of TCMs and HMG-CoA reductase inhibitor in treating hyperlipidemia shows stable efficacy and less adverse reactions, and provides a new option for the combined application of drugs. In this article, the pharmacophore technology was used to search chemical components of TCMs, trace their source herbs, and determine the potential common TCMs that could activate PPAR-α. Because there is no hyperlipidemia-related medication reference in modern TCM classics, to ensure the high safety and efficacy of all selected TCMs, we selected TCMs that are proved to be combined with statins in the World Traditional/Natural Medicine Patent Database, analyzed corresponding drugs in pharmacophore results based on that, and finally obtained common TCMs that can be applied in PPAR-α and combined with statins. Specifically, the pharmacophore model was based on eight receptor-ligand complexes of PPAR-α. The Receptor-Ligand Pharmacophore Generation module in the DS program was used to build the model, optimize with the Screen Library module, and get the best sub-pharmacophore, which consisted of two hydrogen bond acceptor, three hydrophobic groups and 19 excluded volumes, with the identification effectiveness index value N of 2. 82 and the comprehensive evaluation index CAI value of 1. 84. The model was used to screen the TCMD database, hit 5,235 kinds of chemical components and 1 193 natural animals and plants, and finally determine 62 TCMs. Through patent retrieval, we found 38 TCMs; After comparing with the virtual screening results, we finally got seven TCMs.
