Project description:A major goal in the discovery of bioactive natural products is to rapidly identify active compound(s) and dereplicate known molecules from complex biological extracts. The conventional bioassay-guided fractionation process can be time consuming and often requires multi-step procedures. Herein, we apply a metabolomic strategy merging multivariate data analysis and multi-informative molecular maps to rapidly prioritize bioactive molecules directly from crude plant extracts. The strategy was applied to 59 extracts of three Bacopa species (B. monnieri, B. caroliniana and B. floribunda), which were profiled by UHPLC-HRMS2 and screened for anti-lipid peroxidation activity. Using this approach, six lipid peroxidation inhibitors 1‒6 of three Bacopa spp. were discovered, three of them being new compounds: monnieraside IV (4), monnieraside V (5) and monnieraside VI (6). The results demonstrate that this combined approach could efficiently guide the discovery of new bioactive natural products. Furthermore, the approach allowed to evidence that main semi-quantitative changes in composition linked to the anti-lipid peroxidation activity were also correlated to seasonal effects notably for B. monnieri.
Project description:<p><strong>INTRODUCTION:</strong> Interesting data about the family Asteraceae as a new source of Leishmania major dihydroorotate dehydrogenase (LmDHODH) inhibitors are presented. This key macromolecular target for parasites causing neglected diseases catalyzes the fourth reaction of the de novo pyrimidine biosynthetic pathway, which takes part in major cell functions, including DNA and RNA biosynthesis.</p><p><strong>OBJECTIVES:</strong> We aimed to (1) determine LmDHODH inhibitor candidates, revealing the type of chemistry underlying such bioactivity, and (2) predict the inhibitory potential of extracts from new untested plant species, classifying them as active or inactive based on their LC-MS based metabolic fingerprints.</p><p><strong>METHODS:</strong> Extracts from 150 species were screened for the inhibition of LmDHODH, and untargeted UHPLC-(ESI)-HRMS metabolomic studies were carried out in combination with in silico approaches.</p><p><strong>RESULTS:</strong> The IC50 values determined for a subset of 59 species ranged from 148 µg/mL to 9.4 mg/mL. Dereplication of the metabolic fingerprints allowed the identification of 48 metabolites. A reliable OPLS-DA model (R2 > 0.9, Q2 > 0.7, RMSECV < 0.3) indicated the inhibitor candidates; nine of these metabolites were identified using data from isolated chemical standards, one of which-4,5-di-O-E-caffeoylquinic acid (IC50 73 µM)-was capable of inhibiting LmDHODH. The predictive OPLS model was also effective, with 60% correct predictions for the test set.</p><p><strong>CONCLUSION:</strong> Our approach was validated for (1) the discovery of LmDHODH inhibitors or interesting starting points for the optimization of new leishmanicides from Asteraceae species and (2) the prediction of extracts from untested species, classifying them as active or inactive.</p>