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A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition.

Chagas-Paula DA, Zhang T, Da Costa FB, Edrada-Ebel R - Metabolites (2015)

Bottom Line: The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions.The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action.In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes.

View Article: PubMed Central - PubMed

Affiliation: University of Strathclyde, the John Arbuthnott Building, 161 Cathedral Street, Glasgow G4 0RE, UK. febcosta@fcfrp.usp.br.

ABSTRACT
The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential for the treatment of several inflammatory diseases, but there is not much investigation reported in the literature for natural products. In this study, 57 leaf extracts (EtOH-H2O 7:3, v/v) from different genera and species of the Asteraceae family were tested against COX-1 and 5-LOX while HPLC-ESI-HRMS analysis of the extracts indicated high diversity in their chemical compositions. Using O2PLS-DA (R2 > 0.92; VIP > 1 and positive Y-correlation values), dual inhibition potential of low-abundance metabolites was determined. The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions. The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action. In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes.

No MeSH data available.


Related in: MedlinePlus

(a) negative mode, R2 = 0.97; (b) positive mode, R2 = 0.92. Three dimensional O2PLS-DAscore plot of the HRMS data for 57 Asteraceae leaf extracts grouped according to their AI properties to inhibit COX-1 and/or 5-LOX. Sample codes are found in Table 1 and Table S1. The sample codes were colored as follows: Dual inhibition = yellow (B); only COX-1 inhibition = red (C); only 5-LOX inhibition = blue (L); and no inhibition = green (N). Sample codes are found in Table 1 and Table S1.
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metabolites-05-00404-f004: (a) negative mode, R2 = 0.97; (b) positive mode, R2 = 0.92. Three dimensional O2PLS-DAscore plot of the HRMS data for 57 Asteraceae leaf extracts grouped according to their AI properties to inhibit COX-1 and/or 5-LOX. Sample codes are found in Table 1 and Table S1. The sample codes were colored as follows: Dual inhibition = yellow (B); only COX-1 inhibition = red (C); only 5-LOX inhibition = blue (L); and no inhibition = green (N). Sample codes are found in Table 1 and Table S1.

Mentions: O2PLS-DA of the processed HPLC-ESI-HRMS data (Section 2.2.) along with their AI properties found a clear separation among the samples in accordance to their ability to inhibit COX and/or LOX (Figure 4 and Figure 5). The R2 values were 0.97 and 0.92 for the HPLC-ESI-HRMS negative and positive data, respectively. R2 values described the amount of Y variables illustrated by the model after cross-validation which gave an overview of the model fitness. R2 very close to 1.0 was desired, although values >0.5 were considered good values due to the component complexity of the samples [24,77]. However, even for samples with highly complex composition profile (Figures S1 and S2), the R2 values were >0.9, which indicated a significant statistical difference in chemical composition between groups with different AI properties. This implied that each of the active groups of extracts yielded their respective unique group of metabolites that are not present in the non-active extracts as implicated by the clustering three dimensional O2PLS-DAscore plot (Figure 4).


A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition.

Chagas-Paula DA, Zhang T, Da Costa FB, Edrada-Ebel R - Metabolites (2015)

(a) negative mode, R2 = 0.97; (b) positive mode, R2 = 0.92. Three dimensional O2PLS-DAscore plot of the HRMS data for 57 Asteraceae leaf extracts grouped according to their AI properties to inhibit COX-1 and/or 5-LOX. Sample codes are found in Table 1 and Table S1. The sample codes were colored as follows: Dual inhibition = yellow (B); only COX-1 inhibition = red (C); only 5-LOX inhibition = blue (L); and no inhibition = green (N). Sample codes are found in Table 1 and Table S1.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4588803&req=5

metabolites-05-00404-f004: (a) negative mode, R2 = 0.97; (b) positive mode, R2 = 0.92. Three dimensional O2PLS-DAscore plot of the HRMS data for 57 Asteraceae leaf extracts grouped according to their AI properties to inhibit COX-1 and/or 5-LOX. Sample codes are found in Table 1 and Table S1. The sample codes were colored as follows: Dual inhibition = yellow (B); only COX-1 inhibition = red (C); only 5-LOX inhibition = blue (L); and no inhibition = green (N). Sample codes are found in Table 1 and Table S1.
Mentions: O2PLS-DA of the processed HPLC-ESI-HRMS data (Section 2.2.) along with their AI properties found a clear separation among the samples in accordance to their ability to inhibit COX and/or LOX (Figure 4 and Figure 5). The R2 values were 0.97 and 0.92 for the HPLC-ESI-HRMS negative and positive data, respectively. R2 values described the amount of Y variables illustrated by the model after cross-validation which gave an overview of the model fitness. R2 very close to 1.0 was desired, although values >0.5 were considered good values due to the component complexity of the samples [24,77]. However, even for samples with highly complex composition profile (Figures S1 and S2), the R2 values were >0.9, which indicated a significant statistical difference in chemical composition between groups with different AI properties. This implied that each of the active groups of extracts yielded their respective unique group of metabolites that are not present in the non-active extracts as implicated by the clustering three dimensional O2PLS-DAscore plot (Figure 4).

Bottom Line: The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions.The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action.In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes.

View Article: PubMed Central - PubMed

Affiliation: University of Strathclyde, the John Arbuthnott Building, 161 Cathedral Street, Glasgow G4 0RE, UK. febcosta@fcfrp.usp.br.

ABSTRACT
The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential for the treatment of several inflammatory diseases, but there is not much investigation reported in the literature for natural products. In this study, 57 leaf extracts (EtOH-H2O 7:3, v/v) from different genera and species of the Asteraceae family were tested against COX-1 and 5-LOX while HPLC-ESI-HRMS analysis of the extracts indicated high diversity in their chemical compositions. Using O2PLS-DA (R2 > 0.92; VIP > 1 and positive Y-correlation values), dual inhibition potential of low-abundance metabolites was determined. The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions. The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action. In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes.

No MeSH data available.


Related in: MedlinePlus