Synergistic mechanism of traditional Chinese medicine based on target combination of PepT1 and PPARα / 中国中药杂志

Synergistic effect is main pharmacological mechanism of traditional Chinese medicine(TCM). The research method based on the key targets combination is an important method to explore the synergistic effect of TCM. Peptide transporter 1 (PepT1) is an essential target for drug uptake into the bloodstream, accounting for about 50% of the total transporter protein content from the small intestine. Peroxisome proliferator-activated receptor α(PPARα) is the lipid-lowering target of fibrates, which have a good hypolipidemic effect by activating PPARα. It has been reported that PPARα could activate the gene expression of PepT1s, and PPARα agonists can promote the uptake of PepT1 substrates, indicating their synergistic effect. In this paper, PepT1 substrates and PPARα agonists from TCM were discovered, and their synergistic mechanism was also been discussed based on the target combination of PepT1 and PPARα. The support vector machine(SVM) model of PepT1 substrates was first constructed and utilized to predict potential TCM components. Meanwhile, merged pharmacophore and docking model of PPARα agonists was used to screen the potential active ingredients from TCM. According to the analysis results of two groups, the TCM combination of Panax notoginseng and Ganoderma lucidum, as well as TCM combination of P. notoginseng and Salvia miltiorrhiza were identified to have the synergistic mechanism based on target combination of PepT1 and PPARα. In this study, synergistic mechanism of TCM was analyzed for absorption and hypolipidemic effect based on target combination, which provides a new way to explore the synergetic mechanism of TCM related to pharmacokinetics.

Prediction of ETA oligopeptides antagonists from Glycine max based on in silico proteolysis / 中国中药杂志

Oligopeptides are one of the the key pharmaceutical effective constituents of traditional Chinese medicine(TCM). Systematic study on composition and efficacy of TCM oligopeptides is essential for the analysis of material basis and mechanism of TCM. In this study, the potential anti-hypertensive oligopeptides from Glycine max and their endothelin receptor A (ETA) antagonistic activity were discovered and predicted based on in silico technologies.Main protein sequences of G. max were collected and oligopeptides were obtained using in silico gastrointestinal tract proteolysis. Then, the pharmacophore of ETA antagonistic peptides was constructed and included one hydrophobic feature, one ionizable negative feature, one ring aromatic feature and five excluded volumes. Meanwhile, three-dimensional structure of ETA was developed by homology modeling methods for further docking studies. According to docking analysis and consensus score, the key amino acid of GLN165 was identified for ETA antagonistic activity. And 27 oligopeptides from G. max were predicted as the potential ETA antagonists by pharmacophore and docking studies.In silico proteolysis could be used to analyze the protein sequences from TCM. According to combination of in silico proteolysis and molecular simulation, the biological activities of oligopeptides could be predicted rapidly based on the known TCM protein sequence. It might provide the methodology basis for rapidly and efficiently implementing the mechanism analysis of TCM oligopeptides.

Discovery of potential LXRβ agonists from Chinese herbs using molecular simulation methods / 中国中药杂志

Liver X receptor β (LXRβ) has been a new target in the treatment of hyperlipemia, which was related to the cholesterol homeostasis. In this study, the quantitative pharmacophores were constructed by 3D-QSAR pharmacophore (Hypogen) method based on the LXRβ agonists. The optimal pharmacophore model containing one hydrogen bond acceptor, two hydrophobics and one ring aromatic was obtained based on five assessment indictors, including the correlation between predicted value and experimental value of the compounds in training set (correlation), Δcost of the models (Δcost), hit rate of active compounds (HRA), identification of effectiveness index (IEI) and comprehensive evaluation index (CAI). And the values of the five assessment indicators were 0.95, 128.65, 84.44%, 2.58 and 2.18 respectively. The best model as a query to screen the traditional Chinese medicine database (TCMD), a list of 309 compounds was obtained andwere then refined using Libdock program. Finally, based on the screening rules of the Libdock score of initial compound and the key interactions between initial compound and receptor, four compounds, demethoxycurcumin, isolicoflavonol, licochalcone E and silydianin, were selected as potential LXRβ agonists. The molecular simulation methods were high-efficiency and time-saving to obtainthe potential LXRβ agonists, which could provide assistance for further researchingnovel anti-hyperlipidemia drugs.