To construct a model formula to evaluate the thermogenetic effect of ginger (Zingiber officinale Roscoe) from the ingredient information, we established transient receptor potential vanilloid subtype 1 (TRPV1)-stimulating activity prediction models by using a partial least-squares projections to latent structures (PLS) regression analysis in which the ingredient data from liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and the stimulating activity values for TRPV1 receptor were used as explanatory and objective variables, respectively. By optimizing the peak extraction condition of the LC-HRMS data and the data preprocessing parameters of the PLS regression analysis, we succeeded in the construction of a TRPV1-stimulating activity prediction model with high precision ability. We then searched for the components responsible for the TRPV1-stimulating activity by analyzing the loading plot and s-plot of the model, and we identified [6]-gingerol (1) and hexahydrocurcumin (3) as TRPV1-stimulating activity components.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.jafc.7b00577DOI Listing

Publication Analysis

Top Keywords

trpv1-stimulating activity
20
pls regression
12
prediction models
8
transient receptor
8
receptor potential
8
potential vanilloid
8
vanilloid subtype
8
subtype trpv1-stimulating
8
lc-hrms data
8
activity prediction
8

Similar Publications

To construct a model formula to evaluate the thermogenetic effect of ginger (Zingiber officinale Roscoe) from the ingredient information, we established transient receptor potential vanilloid subtype 1 (TRPV1)-stimulating activity prediction models by using a partial least-squares projections to latent structures (PLS) regression analysis in which the ingredient data from liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and the stimulating activity values for TRPV1 receptor were used as explanatory and objective variables, respectively. By optimizing the peak extraction condition of the LC-HRMS data and the data preprocessing parameters of the PLS regression analysis, we succeeded in the construction of a TRPV1-stimulating activity prediction model with high precision ability. We then searched for the components responsible for the TRPV1-stimulating activity by analyzing the loading plot and s-plot of the model, and we identified [6]-gingerol (1) and hexahydrocurcumin (3) as TRPV1-stimulating activity components.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!