GC-MS and HPLC-ESI-MS-MS Characterization of Sanchezia oblonga (Acanthaceae) Extracts


  •  Juliana Mourão Ravasi    
  •  Giuseppina Negri    
  •  Antonio Salatino    
  •  Maria Luiza Faria Salatino    
  •  Marco Aurelio Sivero Mayworm    

Abstract

The genus Sanchezia (Acanthaceae) comprises neotropical herbs and shrubs with showy flowers. Sanchezia oblonga (syn. S. nobilis) is a shrub of the rainforests of central and south America. The ethanolic extracts of leaves and stems from S. oblonga were analyzed by GC-EI-MS and RPHPLC-DAD-ESI-MS/MS. Fatty acids (free and esterified) and phytosterols were detected by the former method. Benzyl alcohol glycosides (21 and 25), sinapic acid glycoside esters (29 and 31), ethyl rosmarinate (24), sinapic acid-O-glucoside (28), dihydrosinapic acid-O-glucoside (26), catechin-O-arabinoside (36), in addition to flavonols glycosides (23, 32, 33 and 35) and rosmarinic acid-3’-O-glucoside (34) were detected by RPHPLC-DAD-ESI-MS/MS. Three new compounds, detected only in leaves, were tentatively identified as phenylpropane glyceride derivatives 1-O-coumaroyl-2-hydroxy propanal (20) and 1-O-coumaroyl-2-O-glycosyl propanal (22, 30). Compounds 20, 22 and 30 from S. oblonga are similar with phenylpropane glycerides present in red sorghum (Sorghum bicolor L. (Moench) and Lilium longiflorum Thunb. It is noteworthy that S. oblonga could be used in cooking as a complement after more detailed studies. Sorghum grain foods exhibit potential health benefits against chronic diseases related to over-nutrition. Lilium longiflorum possess flower buds and bulbs that are used for both culinary and medicinal purposes in many parts of the world. Studies on chemical composition and biological activity of the genus Sanchezia are scarce. The presence of phytosterols and flavonol glycosides were recently reported in leaves from this species. However, the chemical profile of the extracts analyzed in this work differs from that previously reported for aerial parts of S. nobilis (sin. S. oblonga). Further studies, including statistical methods, such as principal component analysis and hierarchical cluster analysis will be needed to evaluate chemical markers for this species.



This work is licensed under a Creative Commons Attribution 4.0 License.