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DOI 10.3390/ijms26062530

Медицинская библиотека · International journal of molecular sciences · 2025

Metabolomic Characterization and Bioinformatic Studies of Bioactive Compounds in Two Varieties of Psidium guajava L. Leaf by GC-MS Analysis.

Valdivia-Padilla Ana Victoria, Sharma Ashutosh, Zegbe Jorge A, Morales-Domínguez José Francisco

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Аннотация

The guava tree (Psidium guajava L.) is a tropical plant from the Myrtaceae family. Leaf extracts from this plant have been used in traditional medicine to treat gastrointestinal disorders and exhibit several functional activities that benefit human health. Different varieties of guava trees produce fruits in colors ranging from white to red and present a characteristic metabolic profile in both their leaves and fruits. This study presents a metabolomic characterization of the leaves from two guava varieties: the Caxcana cultivar with yellow fruits and the S-56 accession with pink fruits. Metabolite profiling was conducted using Gas Chromatography-Mass Spectrometry (GC-MS) on methanol extracts, followed by multivariate statistical analysis, including Principal Component Analysis (PCA), and a heat map visualization of compound concentrations in the two varieties. The results identified β-caryophyllene as the major secondary metabolite present in both varieties, with a relative abundance of 16.46% in the Caxcana variety and 23.06% in the S-56 cultivar. Furthermore, in silico analyses, such as network pharmacology and molecular docking, revealed key interactions with proteins such as CB2, PPARα, BAX, BCL2, and AKT1, suggesting potential therapeutic relevance. These findings highlight the pharmacological potential of guava leaf metabolites in natural product chemistry and drug discovery.

Для цитирования: Valdivia-Padilla Ana Victoria, Sharma Ashutosh, Zegbe Jorge A, Morales-Domínguez José Francisco. Metabolomic Characterization and Bioinformatic Studies of Bioactive Compounds in Two Varieties of Psidium guajava L. Leaf by GC-MS Analysis.. International journal of molecular sciences. 2025. DOI: 10.3390/ijms26062530.

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