The chemical complexity of natural products, such as Eugenia punicifolia (Kunth) DC. plant, presents a challenge when extracting and identifying bioactive compounds. This study investigates the impact of different extraction systems and seasonal variations on the chemical profile and pharmacological potential of E. punicifolia leaves using NMR spectroscopy for chemical analysis and canonical correlation analysis (CCA) for bioactivity correlation. Extracts obtained with methanol (M), ethanol (E), methanol/ethanol (1:1, ME), and methanol/ethanol/water (3:1:1, MEW) were analyzed for antioxidant, antiglycation, and antiviral activities. Quantitative ¹H NMR, combined with the PULCON method, was used to quantify phenolic compounds such as quercetin, myricetin, catechin, and gallic acid. The results showed that the MEW extract obtained in the rainy season exhibited the highest antioxidant and antiglycation activities, with a greater than 93% of advanced-glycation end-products (AGEs) inhibition capacity. Furthermore, our results showed that all the extracts were able to inhibit over 94% of the Zika virus (ZIKV) infection in Vero E6 cells. The CCA established strong correlations between the phenolic compounds and bioactivities, identifying gallic acid, catechin, quercetin, and myricetin as key chemical markers. This study demonstrates the importance of selecting appropriate extraction systems and considering seasonality to optimize the pharmacological potential of E. punicifolia leaves and highlights the efficacy of NMR in linking chemical composition with bioactivities.

The COVID-19 pandemic highlighted the urgent need for effective antiviral therapies against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and its emerging variants. Amazonian biodiversity represents an immeasurable source of natural compounds with unexplored potential against viruses. In this context, Lisboaeflavanonol A (LFA) is a novel glycosyl flavonoid isolated from Eugenia lisboae leaves that was shown by our previous in silico analysis to potentially inhibit the SARS-CoV-2 proteins 3-chymotrypsin-like cysteine protease (3CLpro) and RNA-dependent RNA polymerase (RdRp). Here we aimed to validate the anti-SARS-CoV-2 activity of LFA. This was first assessed using a VSV/SARS-CoV-2 pseudotyped virus system in Vero E6 cells. LFA exhibited a CC₅₀ of 209.7 µg/ml (≈ 370.0 µM), EC₅₀ of 11.6 µg/ml (≈ 20.5 µM), and a selective index (SI) of 18.1. Furthermore, using a SARS-CoV-2_WT infectious clone expressing Neongreen in A549-ACE2-TMPRSS2 cells, LFA had a CC₅₀ and EC₅₀ of 185.7 µg/ml (≈ 327.8 µM) and of 4.6 µg/ml (≈ 8.1 µM), respectively; and SI of 40.4. In time of addition assays, LFA strongly inhibited SARS-CoV-2 at post-entry stages and further characterize the post-entry activity we used a SARS-CoV-2 subgenomic replicon and demonstrated that RNA synthesis was also strongly inhibited by LFA. Finally, LFA showed cross-variant antiviral potential against SARS-CoV-2 Delta and Omicron variants. Our findings suggest that LFA possesses great potential as an antiviral compound and can serve as a scaffold for the development of novel antiviral drugs against SARS-CoV-2.

In recent decades, a new class of solvents known as natural deep eutectic solvents has emerged. In this study, the efficacy of different natural deep eutectic solvents, prepared by ultrasound-assisted synthesis, was evaluated for extracting bioactive compounds from Tapirira guianensis fruits. A total of seven natural deep eutectic solvents systems, combining choline chloride with various hydrogen bond donors (carboxylic acids, alcohols, and sugars), were analyzed for total phenolic content and antioxidant activity. The results showed that carboxylic acid-based natural deep eutectic solvents were the most efficient, with the best results obtained using choline chloride/citric acid/glycerol (Stap7) > choline chloride/citric acid (Stap1) > choline chloride/lactic acid (Stap2), yielding total phenolic contents of 715.7 ± 1.1, 648.5 ± 1.2, and 630.7 ± 0.7 mg GAE/g, respectively. Ultrasonic extraction with 40% (v/v) eutectic mixtures showed that combinations with citric acid were more effective, producing extracts with high concentrations of polyphenols and antioxidant potential. The antioxidant activity, measured by 2,2-Diphenyl-1-picrylhydrazyl, 2,2′-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt, and ferric-reducing antioxidant power assays, showed a similar trend. Spectroscopic analysis (nuclear magnetic resonance) identified gallic acid and 5-hydroxyvanillin, providing structural details of the extracts. Macro- and micronutrient analysis revealed some elements below detection limits. Therefore, these extracts can be used directly for application development without additional isolation.

Glycosides are widely distributed plant metabolites with remarkable structural diversity and broad biological activities. However, comprehensive strategies for their systematic recognition, extraction, and annotation from complex plant matrices remain scarce, especially for chemically underexplored Amazonian species such as Strychnos jobertiana. In this study, we present an integrated analytical strategy combining leaf spray chemical profiling and feature-based molecular networking (FBMN) analysis to guide extract preparation and enable glycoside annotation from S. jobertiana leaves. Rapid chemical profiling by leaf spray mass spectrometry (LS-MS) enabled the early recognition of glycoside-related ions, including alkaloid and flavonoid derivatives, guiding the preparation of an aqueous extract processed by solid-phase extraction (SPE) before liquid chromatography-mass spectrometry (LC-MS) analysis. The resulting data were explored using FBMN supported by spectral search analysis and manual interpretation of tandem mass spectra. In parallel, the isolation of desoxycordifoline (1), harman-3-carboxylic acid (2), kaempferol 3-O-(2”,6”-di-O-rhamnopyranosyl) glucopyranoside (3), and kaempferol-3-O-neohesperidoside (4) provided structural support for the annotation of molecular clusters. Two major glycoside clusters were characterized, one dominated by flavonoid glycosides, and another composed primarily of monoterpene-derived glycosides. Overall, 21 compounds were annotated, including derivatives related to compounds 1-4, such as secoxyloganin (8), kaempferol-3‑O-glucoside (5), kaempferol3-O-rutinoside (6), and kaempferol-3-O-rungioside (7), and diagnostic fragment ions associated with glycoside compounds were highlighted. This integrated workflow demonstrates the value of LS-MS profiling as a decision-making tool for extract preparation and highlights feature-based molecular networking (FBMN) as a powerful approach for glycoside annotation, contributing to the chemical knowledge of Amazonian plant species.

The chemical complexity of natural products such as Eugenia punicifolia (Kunth) DC. plant, presents a challenge when extracting and identifying bioactive compounds. This study investigates the impact of different extraction systems and seasonal variations on the chemical profile and pharmacological potential of E. punicifolia leaves using NMR spectroscopy for chemical analysis and canonical correlation analysis (CCA) for bioactivity correlation. Extracts obtained with methanol (M), ethanol (E), methanol:ethanol [1:1 (ME)], and methanol:ethanol:water [3:1:1 (MEW)] were analyzed for antioxidant, antiglycation and antiviral activities. Quantitative ¹H NMR, combined with the PULCON method, was used to quantify phenolic compounds such as quercetin, myricetin, catechin and gallic acid. The results showed that the MEW extract obtained in the rainy season exhibited the highest antioxidant and antiglycation activities, with an AGE inhibition capacity greater than 93%. Furthermore, our results showed that all the extracts were able to inhibit over 94% of the Zika virus (ZIKV) infection in Vero E6 cells. The CCA established strong correlations between the phenolic compounds and bioactivities, identifying gallic acid, catechin, quercetin and myricetin as key chemical markers. This study demonstrates the importance of selecting appropriate extraction systems and considering seasonality to optimize the pharmacological potential of E. punicifolia leaves and highlights the efficacy of NMR in linking chemical composition with bioactivities.