Metabolomic analysis of the bioactivity in COX and LOX pathways-dependent of plants from subtribe Lychnophorinae

Abstract

The Asteraceae Family is one of the largest families among higher plants (Angiospermae). One of the sub-tribes that belong to this family is the Lychnophorinae, represented by 11 genera and 81 species, distributed in rupestrian fields and the Cerrado of Minas Gerais and Planalto Central. Many compounds of chemical classes present in Lychnophorae species, specially the sesquiterpene lactones or even phenolic compounds, are reported as inhibitors of mediators in the cascade of reactions that result in triggering the inflammatory process. Two enzymes are essential in the metabolism of arachidonic acid formed in the inflammatory process: cyclooxygenases (COX) and lipoxygenase (LOX), promoting the production of eicosanoids such as prostaglandins, prostacyclins and thromboxanes via the COX-dependent pathway in LOX and leukotriene-dependent. In the search for compounds that are responsible for the pharmacological actions, is clear the need for studies using more sensitive, rapid and effective analytical methodologies, such as metabolomics analysis. Obtaining the metabolic fingerprint is the detailed obtaining the metabolites of the organism under certain condition, producing a chromatogram characteristic of that plant, like a fingerprint. Through this, is possible to determinate metabolic differences in samples, by means of statistics tools. For the refinement of the data, it is necessary to use specific softwares to extract useful information for analysis. The information generated can be used for different applicabilities, but it must analyze the data by in silico methods, for which there are several statistical softwares that can be used fulfill these procedures. This project aims to analyze the pharmacological potential of species of the subtribe Lychnophorinae using metabolomic studies as subsidies, linking them with anti-inflammatory in vitro inhibition of cyclooxygenase and lipoxygenase pathways, through correlation analyzes in silico analyzes related.