Article

Investigation of the Influence of the Extraction System and

Seasonality on the Pharmacological Potential of
Eugenia punicifolia Leaves
Kidney O. G. Neves 1 , Samuel O. Silva 1 , Marinildo S. Cruz 1 , Josiana Moreira Mar 2 , Jaqueline A. Bezerra 2 ,
Edgar A. Sanches 2 , Natasha Marques Cassani 3 , Giovanna A. Antoniucci 3 , Ana Carolina Gomes Jardim 3 ,
Francisco C. M. Chaves 4 , Leonard D. R. Acho 5 , Emersom S. Lima 5 , Marcos B. Machado 1, *
and Alan D. C. Santos 1,6, *

1 Núcleo de Estudos Químicos de Micromoléculas da Amazônia—NEQUIMA, Universidade Federal do

Amazonas, Manaus 69067-005, AM, Brazil; kidneydeoliveira@ufam.edu.br (K.O.G.N.);
samuel-oliveira.silva@ufam.edu.br (S.O.S.); marinildo.cruz@ufam.edu.br (M.S.C.)
2 Laboratório de Polímeros Nanoestruturados (NANOPOL), Departamento de Física de Materiais,
Universidade Federal do Amazonas, Manaus 69067-005, AM, Brazil; josimoreira@ufam.edu.br (J.M.M.);
jaqueline.araujo@ifam.edu.br (J.A.B.); sanchesufam@ufam.edu.br (E.A.S.)
3 Laboratory of Antiviral Research, Federal University of Uberlândia, Uberlândia 38405-302, MG, Brazil;
natashacassani@ufu.br (N.M.C.); giovanna.antoniucci@ufu.br (G.A.A.); jardim@ufu.br (A.C.G.J.)
4 Empresa Brasileira de Pesquisa Agropecuária—Embrapa Amazônia Ocidental, Manaus 69010-970, AM, Brazil;
celio.chaves@embrapa.br
5 Laboratório de Atividade Biológica, Faculdade de Ciências Farmacêuticas, Universidade Federal do
Amazonas, Manaus 69067-005, AM, Brazil; leonard.rosale@ufam.edu.br (L.D.R.A.);
eslima@ufam.edu.br (E.S.L.)
6 Núcleo de Pesquisa de Produtos Naturais, Universidade Federal de Santa Maria,
Santa Maria 97105-900, RS, Brazil
* Correspondence: marcosmachado@ufam.edu.br (M.B.M.); alan.santos@ufsm.br (A.D.C.S.)
Academic Editors: Claudio Ferrante,
Irwin Rose Alencar Menezes,
Henrique Douglas Melo Coutinho,
Abstract: The chemical complexity of natural products, such as Eugenia punicifolia (Kunth)
Almir Gonçalves Wanderley and DC. plant, presents a challenge when extracting and identifying bioactive compounds.
Jaime Ribeiro-Filho This study investigates the impact of different extraction systems and seasonal variations
Received: 3 December 2024 on the chemical profile and pharmacological potential of E. punicifolia leaves using NMR
Revised: 23 January 2025 spectroscopy for chemical analysis and canonical correlation analysis (CCA) for bioactivity
Accepted: 27 January 2025 correlation. Extracts obtained with methanol (M), ethanol (E), methanol/ethanol (1:1, ME),
Published: 5 February 2025
and methanol/ethanol/water (3:1:1, MEW) were analyzed for antioxidant, antiglycation,
Citation: Neves, K.O.G.; Silva, S.O.; and antiviral activities. Quantitative ¹H NMR, combined with the PULCON method, was
Cruz, M.S.; Mar, J.M.; Bezerra, J.A.;
used to quantify phenolic compounds such as quercetin, myricetin, catechin, and gallic acid.
Sanches, E.A.; Cassani, N.M.;
The results showed that the MEW extract obtained in the rainy season exhibited the highest
Antoniucci, G.A.; Jardim, A.C.G.;
Chaves, F.C.M.; et al. Investigation of
antioxidant and antiglycation activities, with a greater than 93% of advanced-glycation
the Influence of the Extraction System end-products (AGEs) inhibition capacity. Furthermore, our results showed that all the
and Seasonality on the extracts were able to inhibit over 94% of the Zika virus (ZIKV) infection in Vero E6 cells.
Pharmacological Potential of Eugenia The CCA established strong correlations between the phenolic compounds and bioactiv-
punicifolia Leaves. Molecules 2025, 30,
ities, identifying gallic acid, catechin, quercetin, and myricetin as key chemical markers.
713. https://doi.org/10.3390/
This study demonstrates the importance of selecting appropriate extraction systems and
molecules30030713
considering seasonality to optimize the pharmacological potential of E. punicifolia leaves
Copyright: © 2025 by the authors.
and highlights the efficacy of NMR in linking chemical composition with bioactivities.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
Keywords: pedra-ume-caá; medicinal plant; solvent extraction; antioxidant; antiglycation;
distributed under the terms and
conditions of the Creative Commons
antiviral; Zika virus; phenolic compounds; NMR spectroscopy; CCA
Attribution (CC BY) license
(https://creativecommons.org/
licenses/by/4.0/).

Molecules 2025, 30, 713 https://doi.org/10.3390/molecules30030713

Molecules 2025, 30, 713 2 of 16

1. Introduction
Eugenia punicifolia (Kunth) DC., a species that is both native and endemic to Brazil,
is widely distributed throughout the Amazon region. Commonly known as a “vegetable
insulin”, this plant is part of a group of species known as pedra-ume-caá, which are tra-
ditionally used in herbal medicine [1–3]. Research on this matrix has demonstrated that
its leaves contain barbinervic acid, a compound with vasodilatory effects. This compound
shows significant potential as a template for developing new molecules to treat cardio-
vascular diseases [4]. Basting et al. (2014) demonstrated that the hydroalcoholic extract
from the leaves has significant antinociceptive and anti-inflammatory effects, which may
be related to the inhibition of the glutamatergic system, nitric oxide synthesis, and the phos-
phorylation of p38α MAPK [5]. Furthermore, Oliveira et al. (2022), Sales et al. (2014), and
Ramos et al. (2019) showed that the leaves and fruits of this species exhibit antioxidant and
antiglycation potential, as well as a chemical composition rich in flavonoids and organic
acids with various pharmacological properties, particularly for the treatment of diabetes
mellitus [2,6,7]. E. punicifolia is frequently marketed in the Amazon for this purpose. Its
widespread use in this region has driven scientific interest in exploring its pharmacological
potential, especially its ability to manage blood glucose levels in diabetic patients [2,6–9].
In general, natural products are chemically complex and contain a wide variety of
bioactive compounds, including alkaloids, flavonoids, terpenes, lignoids, and phenolic
acids, each contributing to the plant’s overall pharmacological activity. This complexity,
coupled with the typically low concentrations of these bioactive compounds, poses signifi-
cant challenges in the chemical analysis of such matrices, making the choice of extraction
methodology crucial. Extraction serves as the initial step to isolate the desired bioactive
compounds from the raw material and can provide a clear snapshot of the plant’s chemical
profile, while the type of extraction used can maximize both the yield and selectivity of
active principles [10].
This matter has been exemplified in the work published by Neves et al. (2004), who
investigated the influence of seasonal variation (dry, rainy, and transition periods) on the
¹H NMR chemical profiles and antioxidant potential of E. punicifolia leaf extracts obtained
with dimethyl sulfoxide (DMSO) [11]. Although variations in the chemical profiles and
antioxidant activities were observed between the seasons, the ¹H NMR data did not provide
sufficient insight into the correlation between secondary metabolites and bioactivity, since
DMSO favored the extraction of primary metabolites. This limitation highlights the need
to explore alternative extraction methods to better establish the link between secondary
metabolites and bioactivity.
Although several studies have reported extraction methods for analyzing the chem-
ical composition of E. punicifolia, only a few have investigated or optimized these pro-
cesses to assess their impact on biological activity [9,12,13]. Among them, the work of
Santos et al. (2020) stands out for its focus on optimizing the recovery of phenolic com-
pounds with enhanced antioxidant and antiproliferative activities. Using a multivariate
analytical approach, they developed an optimized extraction method for E. punicifolia leaves.
Among the solvents tested (ethanol, methanol, and water), ethanolic extracts yielded the
highest phenolic content, exhibited the strongest antioxidant activity, and demonstrated
moderate antiproliferative activity against HEp-2 cells [9]. Santos et al.’s (2020) study
provides a solid foundation for research on extraction methods for E. punicifolia and served
as the starting point for our current investigation.
Nuclear magnetic resonance spectroscopy (NMR) has played an important role in
tracking the qualitative and quantitative profiles of metabolites in plants, offering relevant
insight into their complex chemical compositions [14–16]. This technique is essential
for establishing correlations between the chemical profiles of plant extracts and their
Molecules 2025, 30, 713 3 of 16

biological activities, often referred to as spectrum–effect relationships [17–19]. By providing

detailed molecular information, NMR allows researchers to link specific metabolites to
pharmacological effects, aiding in the identification of key bioactive compounds and
optimizing the extraction methods for targeted applications.
In this context, the present study aimed to identify the most effective extraction solvent
for correlating the quantitative chemical profiles, obtained through NMR spectroscopy, with
the pharmacological potential (antioxidant, antiglycation, and antiviral) of E. punicifolia
leaves collected during different seasonal periods.

2. Results and Discussion

2.1. The Performance of the Extraction Systems Tested
Water, methanol, ethanol, their mixtures, and aqueous acetone solutions are commonly
used for the extraction of phenolic compounds [9]. However, the wide diversity of phenolics
in plants poses a challenge to the standardization of extraction methods, particularly in
selecting the most suitable solvent [9,11].
The efficiency of the extraction system was evaluated by calculating the mean and
standard deviation of yield values obtained in triplicate (Table 1). The ternary mixture MEW
(methanol/ethanol/water) produced the highest yields, with overall standard deviations
ranging from 7.31% to 13.46%. The method’s reproducibility was assessed using an ANOVA
of the mean yields, considering both the extraction solvent and the collection period. This
analysis demonstrated satisfactory reproducibility, as no significant statistical differences in
extraction yields were observed across samples collected in different periods as a function
of the extraction solvent—except for the samples collected during the dry season and
extracted with methanol. This indicates that the extraction efficiency is slightly affected by
the season, though it confirms that, overall, the extraction systems are suitable for obtaining
E. punicifolia leaf extracts.

Table 1. Yields of E. punicifolia leaf extracts according to the extraction system and collection period.

MEW M EM E
Sample (mg g−1 (mg g−1 (mg g−1 (mg g−1
Dry Extract) Dry Extract) Dry Extract) Dry Extract)
Dry 312.2 ± 13.5 ab 275.8 ± 5.9 c 207.4 ± 4.7 e 117.0 ± 8.9 f
Transition 334.1 ± 7.3 a 298.9 ± 8.6 b 224.9 ± 1.9 ed 118.9 ± 7.8 f
Rainy 328.2 ± 8.1 a 304.2 ± 1.9 b 242.9 ± 9.1 d 124.4 ± 7.1 f
a, b, c, d, e, f
Clustering for extraction yield using Tukey’s test and a 95% confidence interval. Extract acronyms:
MEW—methanol/ethanol/water; M—methanol; EM—ethanol/methanol; and E—ethanol.

2.2. Bioactivities of the E. punicifolia Leaf Extracts

2.2.1. Cytotoxicity of Eugenia punicifolia Leaf Extracts
Cytotoxicity, or assessing cell viability, is a critical step in evaluating the antiviral
potential of plant extracts and substances, as it indicates the ability of a substance or extract
to cause cellular damage or death [20]. In this study, to investigate potential cytotoxicity,
Vero E6 cells (kidney tissue derived from a normal, adult African green monkey) were each
treated with E. punicifolia extracts at the concentrations of 50, 10, and 2 µg mL−1 for 72 h.
Then, cell viability was assessed via an MTT assay. DMSO (0.1%) was used as the untreated
control. Analyzing the effects of the tested extracts on cell viability, we found that the
treatment of Vero E6 cells with extracts at the concentration of 50 µg mL−1 presented cell
viability over 90% (Figure S1).
 2 μg mL−1 for 72 h. Then, cell viability was assessed via an MTT assay. DMSO (0.1%) was
used as the untreated control. Analyzing the effects of the tested extracts on cell viability,
Molecules 2025, 30, 713
we found that the treatment of Vero E6 cells with extracts at the concentration of 50 μg
4 of 16
mL−1 presented cell viability over 90% (Figure S1).

2.2.2.
2.2.2.Anti-ZIKV
Anti-ZIKVActivity
Activity
Due
Due to its traditionaluse
to its traditional useininthethetreatment
treatment ofoftype
type2 diabetes
2 diabetes mellitus,
mellitus, research on on
research E.
punicifolia hashas
E. punicifolia primarily
primarilyfocused
focused ononevaluating
evaluating itsits
antiglycation
antiglycationpotential
potential[2,6,7].
[2,6,7].However,
However,
given
given the species’ diverse chemical composition and its use in regions frequentlyaffected
the species’ diverse chemical composition and its use in regions frequently affected
by
by viruses, including ZIKV, it is crucial to investigate its potential antiviral properties. In
viruses, including ZIKV, it is crucial to investigate its potential antiviral properties. In
this
thisstudy,
study, the
the anti-ZIKV
anti-ZIKV activity
activity ofofthe
theextracts
extractswas wasassessed
assessedusing
usingVero
Vero E6 E6 cells
cellsinfected
infected
with
with ZIKV
ZIKVPE243 in the presence or absence of the extracts for 72 h. The results showed that
PE243 in the presence or absence of the extracts for 72 h. The results showed that
the
the extracts at theestablished
extracts at the establishednon-cytotoxic
non-cytotoxicconcentration
concentrationwere wereable
abletotoinhibit
inhibitup uptoto100%
100%
of
of ZIKV infection, with the minimum inhibitory rate of 94.8% under treatment with the
ZIKV infection, with the minimum inhibitory rate of 94.8% under treatment with the
M-Transition
M-Transitionextract
extract(Figure
(Figure1).1).This
Thisis the first
is the study
first to demonstrate
study to demonstrate thatthat
E. punicifolia leaf
E. punicifolia
extracts can inhibit
leaf extracts ZIKVZIKV
can inhibit replication, whichwhich
replication, enhances the value
enhances the of this of
value plant
thisspecies. How-
plant species.
ever, additional assays should be performed to better understand
However, additional assays should be performed to better understand the mechanism of the mechanism of action
of theseofextracts
action and their
these extracts andcytotoxic effects,effects,
their cytotoxic since they
sincewere
they tested in a general
were tested MTT MTT
in a general and
infection
and infection assay. The observed reduction in viral replication could be a result of eitheraa
assay. The observed reduction in viral replication could be a result of either
virucidal
virucidal activity
activity oror inhibition
inhibition ofof viral
viral replication
replication cyclecycle within
within the
the host
host cells.
cells.

Figure
Figure1.1.Effect
Effectof
ofextracts
extractsofofE.E.punicifolia
punicifolialeaves
leaveson
onviability
viabilityofofVero
VeroE6 E6cells
cellsand
andZIKV
ZIKVinfectivity.
infectivity.
Vero
Vero E6 cells were infected with ZIKVPE243 PE243at
atan
anMOI
MOI of
of 0.01
0.01 in
in the
the presence
presence or
or absence
absence of
of each
each
extract at the highest non-cytotoxic concentration for 72 h. Then, the cells were
extract at the highest non-cytotoxic concentration for 72 h. Then, the cells were fixed, and an immu-fixed, and an
immunofluorescence
nofluorescence assay
assay was was performed.
performed. Focus-forming
Focus-forming units (FFUs)
units (FFUs) were counted.
were counted. The viability
The viability assay
assay was performed in parallel by treating Vero E6 cells with each compound
was performed in parallel by treating Vero E6 cells with each compound at the previously estab- at the previously
established
lished non-cytotoxic
non-cytotoxic concentration,
concentration, and absorbance
and absorbance was measured
was measured (560DMSO
(560 nm). nm). DMSO
(0.1%)(0.1%) was
was used
used as the untreated control. The mean values of two independent experiments, each performed
as the untreated control. The mean values of two independent experiments, each performed in trip-
in triplicate, including the standard error of the mean, are shown. P values < 0.05 were considered
licate, including the standard error of the mean, are shown. P values < 0.05 were considered signif-
significant. (****) p < 0.0001. Extract acronyms: MEW—methanol/ethanol/water; M—methanol;
icant. (****) p < 0.0001. Extract acronyms: MEW—methanol/ethanol/water; M—methanol; EM—eth-
EM—ethanol/methanol; and E—ethanol.
anol/methanol; and E—ethanol.
2.2.3. Antioxidant Activity via DPPH and ABTS Assays
DPPH and ABTS assays provide a low-cost and efficient method for determining the
oxidation-inhibiting capacity of plant-derived substances and extracts [21,22]. As such,
these assays can be used as probes to assess the impact of external factors on the chemical
composition of plant matrices [23,24].
Molecules 2025, 30, 713 5 of 16

The DPPH and ABTS assays demonstrated that, regardless of the extraction system
used, samples collected during the rainy season exhibited the strongest antioxidant re-
sponses (Table 2). Among the extraction systems, EM and MEW yielded the best results;
however, MEW showed an antioxidant response of 8% to 16%, which is higher than that
of the samples extracted with EM. The Pearson correlation for the antioxidant assays was
0.923 (p < 0.05), indicating a strong correlation between the assays and confirming the
antioxidant potential of the samples collected during the rainy season and extracted using
the MEW system.

Table 2. Scavenging capacity of the DPPH• free-radical and the ABTS•+ cation radical expressed in
µM TE g−1 .

Dry Transition Rainy

Sample
DPPH• ABTS•+ DPPH• ABTS•+ DPPH• ABTS•+
MEW 1317.5 ± 6.6 a 1848.8 ± 6.9 a 1449.2 ± 8.8 a 2008.8 ± 8.4 a 1530.8 ± 5.2 a 2121.0 ± 6.7 a
EM 1139.2 ± 10.1 b 1702.1 ± 10.7 b 1213.3 ± 8.0 b 1766.5 ± 6.9 b 1343.33 ± 8.0 b 1919.9 ± 8.4 b
E 1115.0 ± 9.0 c 1685.4 ± 6.9 b 1189.2 ± 8.8 c 1751.0 ± 6.7 b 1318.3 ± 6.3 c 1827.7 ± 6.7 d
M 1025.8 ± 5.2 d 1645.4 ± 8.4 c 1085.8 ± 3.8 d 1703.2 ± 10.2 a 1140.8 ± 7.6 d 1878.8 ± 8.4 c
a, b, c, d
Clustering for scavenging capacity using ANOVA (Tukey’s test and 95% confidence interval). Extract
acronyms: MEW—methanol/ethanol/water; M—methanol; EM—ethanol/methanol; and E—ethanol.

2.2.4. Antiglycation Activity Assay: Non-Oxidative Pathway

Type 2 diabetes mellitus, characterized by persistent hyperglycemia, leads to non-
enzymatic glycation reactions with proteins and lipids, marking the initial stage in the
formation of advanced-glycation end-products (AGEs) [25]. Since AGEs play a critical role
in diabetic complications, identifying plant matrices rich in compounds that can inhibit
the glycation process has become a promising and effective approach. In this study, the
ability of various E. punicifolia leaf extracts to inhibit AGE formation via the non-oxidative
pathway was evaluated (Table 3).

Table 3. Inhibitory capacity of E. punicifolia leaf extracts on the formation of advanced-glycation

end-products via the non-oxidative pathway.

MEW M EM E
Sample
(% Inhibition of AGEs) (% Inhibition of AGEs) (% Inhibition of AGEs) (% Inhibition of AGEs)
Dry 80.5 ± 1.4 b 90.1 ± 2.0 a 80.4 ± 3.0 b 76.0 ± 1.8 b
Transition 94.3 ± 1.5 a 82.4 ± 2.4 b 83.4 ± 1.6 b 94.0 ± 3.0 a
Rainy 93.1 ± 3.7 a 88.2 ± 3.8 ab 94.8 ± 1.4 a 87.5 ± 3.0 a
a, b
Clustering for inhibition of AGEs using ANOVA with Tukey’s test and 95% confidence interval. Extract
acronyms: MEW—methanol/ethanol/water; M—methanol; EM—ethanol/methanol; and E—ethanol.

The results demonstrate that all the extracts exhibited an inhibition potential greater
than 75%. Furthermore, with the exception of the methanol extracts, significant differences
in inhibition capacities were observed between the samples collected during the dry and
rainy seasons. The rainy season samples showed up to 15% higher inhibition compared
to those collected in the dry season. This finding confirms that the collection period is a
critical factor when evaluating the antiglycation potential of E. punicifolia leaves.

2.3. Identification of Phenolic Compounds in E. punicifolia Leaf Extracts

The four extracts (E, M, EM, and MEW) of E. punicifolia leaves were analyzed via
NMR spectroscopy, which led to the identification of gallic acid (1) and four flavonoids:
epigallocatechin (2), catechin (3), quercetin (4), and myricetin (5) (Figures S2–S6). Gallic
acid was identified by correlating the signal at δ 6.95 (H-2 and H-6, s) with the signals
 epigallocatechin (2), catechin (3), quercetin (4), and myricetin (5) (Figures S2–S6). Galli
acid was identified by correlating the signal at δ 6.95 (H-2 and H-6, s) with the signal
Molecules 2025, 30, 713 6 of 16
observed at 165.7 (COOH), 108.6 (C-2 and C-6), 145.6 (C-3 and C-5), and 138.2 (C-4) in th
long-range H- C HMBC correlation map [26]. While the signals at δ 5.89 (H-8, d, 2.3 Hz
1 13

δ 5.72 (H-6, atd,165.7

observed 2.3 Hz),
(COOH), δ 6.38(C-2
and 108.6 (H-2′
andand
C-6),H-5′,
145.6s)
(C-3were
andattributed
C-5), and 138.2to rings
(C-4)Ainand B o
1 H-13 C HMBC correlation map [26]. While the signals at δ 5.89 (H-8, d,
epigallocatechin, along with the singlet at δ 4.73 (H-2, s) and the multiplet at δ 4.00 (H-3
the long-range
m) 2.3 Hz), δ 5.72
referring (H-6,
to its C d, 2.3 Hz),
ring [27].and
Theδ 6.38 (H-2′ and
presence H-5′ , s) were
of catechin attributed
in the extracts to rings
was A and
supported b
B of epigallocatechin, along with the singlet at δ 4.73 (H-2, s) and the multiplet at δ 4.00
signals at δ 5.83 (H-6, d, 2.3 Hz), δ 5.93 (H-8, d, 2.3 Hz), δ 6.65 (H-5′, d, 8.1 Hz), δ 6.75 (H
(H-3, m) referring to its C ring [27]. The presence of catechin in the extracts was supported
6′, dd, 2.3 Hz and 8.1 Hz), and δ 6.86 (H-2′, d, 2.3 Hz), corresponding to rings A and B, a
by signals at δ 5.83 (H-6, d, 2.3 Hz), δ 5.93 (H-8, d, 2.3 Hz), δ 6.65 (H-5′ , d, 8.1 Hz), δ 6.75
well as′ ,the
(H-6 dd, doublet
2.3 Hz and δ 5.02
at 8.1 Hz), (H-2, d, 1.8
and δ 6.86 (H-2Hz)
′ , d,referring to the C ringto[28].
2.3 Hz), corresponding rings Quercetin
A and an
myricetin
B, as well both exhibited
as the doublet atsignals at δ 6.41
δ 5.02 (H-2, d, 1.8(H-8, d, 2.1 Hz)
Hz) referring and
to the δ 6.22
C ring (H-6,
[28]. d, 2.1 Hz) be
Quercetin
longing to ring A;
and myricetin bothhowever,
exhibitedin ring B,
signals at δmyricetin
6.41 (H-8, d, presented
2.1 Hz) and a signal at δ 7.01
δ 6.22 (H-6, d, 2.1(H-2′
Hz) and H
belonging to ring A; however, in ring B, myricetin presented a signal at δ 7.01 (H-2 ′ and
5′, s), while quercetin displayed signals at δ 7.30 (H-2′, d, 2.1 Hz), δ 7.25 (H-6′, dd, 2.1 an
′ (H-2′ , d, 2.1 ′ , dd, 2.1
8.3 H-5
Hz),, s), while
and quercetin
δ 6.87 (H-5′,displayed
d, 8.3 Hz) signals
[28].atThe
δ 7.30
connection ofHz),
the δB7.25
ring (H-6
with the C ring o
′
and 8.3 Hz), and δ 6.87 (H-5 , d, 8.3 Hz) [28]. The connection of the B ring with the C ring
the flavonoids was assigned based on the correlations observed in the HMBC correlatio
of the flavonoids was assigned based on the correlations observed in the HMBC correlation
plot, as shown in Figure 2.
plot, as shown in Figure 2.

Figure 2. Compounds identified by NMR spectroscopy in different E. punicifolia leaf extracts. Blue
Figure 2. Compounds identified by NMR spectroscopy in different E. punicifolia leaf extracts. Blu
arrows represent key correlations observed in the long-range HMBC correlation plot.
arrows represent key correlations observed in the long-range HMBC correlation plot.
2.4. qNMR of Phenolic Compounds by PULCON
2.4. qNMR of Phenolic
PULCON (PulseCompounds by Concentration
Length-Based PULCON Determination) is a powerful NMR
method for quantifying compounds in complex mixtures without requiring specific stan-
PULCON (Pulse Length-Based Concentration Determination) is a powerful NMR
dards for the compounds of interest [29,30]. The method is based on the principle of
method for quantifying compounds in complex mixtures without requiring specific stand
reciprocity, which correlates the absolute intensities in two one-dimensional (1D) NMR
ards for the
spectra compounds
[31,32]. of interest
Using PULCON, the 1 H[29,30]. The method
NMR signals is based
corresponding on acid
to gallic the (δ
principle
6.96, s), of rec
procity, which correlates
epigallocatechin (δ 5.89, d,the
2.3 absolute intensities
Hz), catechin (δ 5.93, d,in2.3
two
Hz),one-dimensional
quercetin (δ 7.30, d,(1D) NMR spec
2.1 Hz),
tra and myricetin
[31,32]. Using (δ PULCON,
7.01, s) werethequantified
1 H NMR in the different
signals extracts of E. to
corresponding punicifolia leaves
gallic acid (δ 6.96, s
(Figures S7–S12), as summarized in Table 4. Overall, the concentrations of compounds
in the E. punicifolia extracts can be categorized into three groups: (I) catechin as the most
abundant phenolic compound, (II) gallic acid and epigallocatechin at intermediate concen-
trations and (III) quercetin and myricetin as the least abundant. The specific ranking within
groups II and III depended on the extraction solvent used and the period considered.
Molecules 2025, 30, 713 7 of 16

Table 4. 1 H NMR quantification of the main phenolic compounds of E. punicifolia leaf extracts
using PULCON.

Sum of Total
Quercetin Myricetin Gallic Acid Catechin Epigallocatechin
Phenolics
Sample (mg g−1 (mg g−1 (mg g−1 (mg g−1 (mg g−1
(mg g−1
Dry Extract) Dry Extract) Dry Extract) Dry Extract) Dry Extract)
Dry Extract)
E—Dry 1.94 ± 0.01 1.40 ± 0.00 3.49 ± 0.01 5.02 ± 0.01 3.34 ± 0.01 15.24 ± 0.20
E—Transition 2.23 ± 0.01 1.62 ± 0.00 3.54 ± 0.01 4.65 ± 0.02 3.63 ± 0.02 15.75 ± 0.31
E—Rainy 2.23 ± 0.00 1.69 ± 0.00 3.50 ± 0.01 4.54 ± 0.01 3.55 ± 0.01 15.60 ± 0.17
EM—Dry 1.24 ± 0.01 1.45 ± 0.01 3.23 ± 0.01 5.50 ± 0.02 3.60 ± 0.02 15.09 ± 0.37
EM—Transition 1.73 ± 0.00 1.71 ± 0.00 4.04 ± 0.01 6.55 ± 0.01 5.01 ± 0.00 19.13 ± 0.18
EM—Rainy 2.44 ± 0.00 1.87 ± 0.00 3.61 ± 0.01 5.78 ± 0.01 4.47 ± 0.00 18.27 ± 0.07
M—Dry 1.47 ± 0.00 1.75 ± 0.01 3.85 ± 0.02 6.54 ± 0.03 4.28 ± 0.02 17.98 ± 0.43
M—Transition 2.07 ± 0.00 1.60 ± 0.00 4.00 ± 0.02 6.35 ± 0.01 5.55 ± 0.01 19.65 ± 0.18
M—Rainy 2.29 ± 0.01 1.83 ± 0.01 3.91 ± 0.00 5.89 ± 0.02 5.08 ± 0.01 19.11 ± 0.43
MEW—Dry 2.89 ± 0.01 2.13 ± 0.00 3.38 ± 0.03 6.97 ± 0.03 4.87 ± 0.03 20.35 ± 0.35
MEW—Transition 2.70 ± 0.01 1.56 ± 0.01 3.91 ± 0.01 6.67 ± 0.03 5.85 ± 0.02 20.94 ± 0.56
MEW—Rainy 3.16 ± 0.00 1.98 ± 0.00 3.79 ± 0.02 6.12 ± 0.01 5.07 ± 0.01 20.22 ± 0.27
Extract acronyms: MEW—methanol/ethanol/water; M—methanol; EM—ethanol/methanol; and E—ethanol.

Table 4 also presents the NMR-quantified phenolic compounds, representing the sum
of all the identified and quantified phenolic compounds. These values clearly demonstrate
the influence of the extraction procedure on the selectivity of phenolic compounds, with
MEW being the most selective solvent and E the least selective. Notably, the total phenolic
content suggested a dependency between the extraction solvent’s selectivity and the periods
(dry, transition, and rainy). For the MEW samples, no significant statistical differences in
total phenolics were observed among the periods. In contrast, extractions with E showed
significant seasonal variation.
The phenolic content provided by PULCON can be a valuable tool in understanding
the relationship between the chemical composition and biological activity of E. punicifolia
leaf extracts, especially since their phenolic profiles are qualitatively similar. In such cases,
differences in biological activities may be linked to variations in phenolic content.

2.5. Chemical Composition and Bioactivities of the E. punicifolia Leaf Extracts: Searching
for Correlations
The correlation between the compounds quantified via 1 H NMR and the pharmaco-
logical potential of E. punicifolia leaf extracts (Figure 3) was assessed using a canonical
correlation analysis (CCA), a multivariate statistical technique that identifies and quan-
tifies the relationship between two sets of variables [33]. Pearson’s correlation coeffi-
cient was applied as the index to evaluate the strength or existence of this correlation
(Table S1) [34,35].
An analysis of the Pearson correlation values with the antioxidant assays revealed
that 2-epigallocatechin (r = 0.67), quercetin (r = 0.87), and myricetin (r = 0.65) exhibit a
moderately positive correlation with the ABTS radical cation scavenging capacity. Addi-
tionally, only quercetin (r = 0.85) and myricetin (r = 0.58) were found to correlate with the
DPPH radical scavenging capacity (Figure 3). Several studies on these flavonoids have
demonstrated their ability to scavenge free radicals in the body [36,37].
 moderately positive correlation with the ABTS radical cation scavenging capacity. Addi-
tionally, only quercetin (r = 0.85) and myricetin (r = 0.58) were found to correlate with the
DPPH radical scavenging capacity (Figure 3). Several studies on these flavonoids have
Molecules 2025, 30, 713 8 of 16
demonstrated their ability to scavenge free radicals in the body [36,37].

Figure 3. Canonical correlation analysis. Pearson correlation coefficients (⋆, r > 0.50) between the
Figure 3. Canonical
concentrations correlation
determined 1 H NMRPearson
usinganalysis. correlationcapacity
and the scavenging of the(★,
coefficients r > 0.50)
DPPH between
radical (A), the
the ABTS radical
concentrations cation (B),using
determined and AGE formation
1H NMR inhibition
and the (C) 1—gallic
scavenging capacityacid, 2—epigallocatechin,
of the DPPH radical (A), the
3—catechin,
ABTS 4—quercetin,
radical cation andAGE
(B), and 5—myricetin.
formation inhibition (C) 1—gallic acid, 2—epigallocatechin, 3—
catechin,In4—quercetin,
2024, a study and 5—myricetin.
on the antioxidant potential of DMSO extracts of E. punicifolia leaves
revealed that samples collected during the dry period exhibited the strongest antioxidant
In 2024,
response a study
[11]. on the antioxidant
This supports the notion that potential of DMSO
the extraction extracts
system of E.
is a key punicifolia
factor since itleaves
revealed that
influences notsamples
only thecollected
antioxidant during
activitythebut
dry period
also exhibited the strongest
any pharmacological activity ofantioxidant
plant
response
matrices.[11].
For This supports
E. punicifolia, the notion
DMSO thatprimarily
extraction the extraction
favored system is a keyand
carbohydrates factor
fattysince it
influences not only
acids, whereas the antioxidant
the extraction systems activity
describedbut alsostudy
in this any pharmacological
favored flavonoid compounds.activity of plant
Among the identified flavonoids, myricetin was notably absent
matrices. For E. punicifolia, DMSO extraction primarily favored carbohydrates and fatty in the DMSO-extracted
samples.
acids, Giventhe
whereas myricetin’s highsystems
extraction antioxidant potential,in
described its this
presence
study likely contributes
favored to the com-
flavonoid
differences in antioxidant capacity observed between the various extraction systems [38].
pounds. Among the identified flavonoids, myricetin was notably absent in the DMSO-
These findings highlight the need to establish a standardized extraction protocol to ensure
extracted samples. Given myricetin’s high antioxidant potential, its presence likely con-
the chemical profile is consistent and serves as a reliable basis for comparison between
tributes to the differences in antioxidant capacity observed between the various extraction
studies on plant matrices.
systems In[38].
the AGEThese findings
formation highlight
inhibition the the
assay, need to establish
Pearson’ a standardized
correlation extraction
analysis revealed that pro-
tocol
onlytogallic
ensureacidthe (r =chemical profile is consistent
0.60), 2-epigallocatechin and and
(r = 0.50), serves as a reliable
myricetin (r = 0.48)basis for compar-
showed a
ison betweenpositive
moderately studiescorrelation
on plant matrices.
(Figure 3). Studies on these compounds demonstrate their
In the
crucial AGE
role formationthe
in inhibiting inhibition
early stages assay, the Pearson'
of glycation, thuscorrelation
preventing analysis revealed
the formation of that
AGEs
only [39].acid
gallic Furthermore,
(r = 0.60),Wang et al. (2024) reported
2-epigallocatechin that myricetin
(r = 0.50), and its derivatives
and myricetin can
(r = 0.48) showed a
completely inhibit products generated by non-enzymatic glycation
moderately positive correlation (Figure 3). Studies on these compounds demonstrate their reactions [40]. Along
with their
crucial role association
in inhibiting withthethe antiglycation
early stages of activity of E.thus
glycation, punicifolia leaves,the
preventing gallic acid,
formation of
catechin, and myricetin have also been suggested by Oliveira et al. (2024) as key chemical
AGEs [39]. Furthermore, Wang et al. (2024) reported that myricetin and its derivatives can
markers for species of Pedra-ume-caá [2].
completely inhibit products generated by non-enzymatic glycation reactions [40]. Along
Given that all E. punicifolia extracts demonstrated variable cytotoxicity in Vero E6 cells
with their
and a ZIKV association with thecapacity
infection inhibition antiglycation activity
greater than 95%, ofthisE.response
punicifolia leaves,
is likely gallic acid,
attributed
catechin, and myricetin have also been suggested by Oliveira
to the phenolic compounds identified and quantified in the extracts [41,42]. Some com- et al. (2024) as key chemical
markers
ponentsfor of species
the extractsof Pedra-ume-caá
enhanced cell [2]. viability at certain concentrations, and this might
be Given thatfact
due to the all that
E. punicifolia
plant-derived extracts demonstrated
polyphenols, including variable
flavonoids,cytotoxicity in Vero E6
exhibit antiox-
cells and
idant a ZIKV infection
properties that support inhibition capacity
cell survival and greater than 95%,
growth under certain this response[43,44].
conditions is likely at-
Myricetin has shown concentration-dependent protective effects,
tributed to the phenolic compounds identified and quantified in the extracts [41,42]. Some enhancing cellular repair
and proliferation
components of theat optimalenhanced
extracts levels [44].cellLikewise,
viability quercetin
at certain hasconcentrations,
been linked to improved
and this might
mitochondrial function and increased metabolic activity, aiding cell viability, especially
be due to the fact that plant-derived polyphenols, including flavonoids, exhibit antioxi-
under stress, which can further be seen by different effects in different concentrations [45].
dant properties that support cell survival and growth under certain conditions [43,44].
Regarding the antiviral properties, a study by Lim et al. (2017) showed that myricetin
Myricetin has shown concentration-dependent protective effects, enhancing cellular re-
can inhibit 88% of ZIKVNS2B-NS3 activity [46]. Similarly, an in vitro study by Zou et al.
pair andfound
(2020) proliferation at optimal of
that, at a concentration levels [44].
1.0 mM, Likewise,
myricetin and quercetin
quercetin can hasinhibit
beenup linked
to to
80% of ZIKVNS1 infection, as also found by Ramos et al. (2022), with quercetin inhibiting
ZIKVNS5 RNA-dependent RNA polymerase (RdRp) with IC50 values of 0.5 µM [47]. This
Molecules 2025, 30, 713 9 of 16

inhibitory capacity has been linked to the presence of hydroxyl groups on ring B of these
compounds [48].
Thus, the canonical correlation analysis, with the Pearson’s correlation coefficient
as an index, proved to be an effective approach, allowing for the identification of gallic
acid, catechin, quercetin, and myricetin as chemical indicators for monitoring the antioxi-
dant, antiglycation, and antiviral activities of E. punicifolia leaf extracts in relation to the
collection period.

3. Materials and Methods

3.1. Materials
The methanol (HPLC) and absolute ethanol (99.5% PA) used for plant material extrac-
tion were purchased from Sigma-Aldrich (St. Louis, MO, USA). The deuterated dimethyl
sulfoxide (DMSO-d6, 99.9%) with tetramethylsilane (TMS, 0.05% V/V) for NMR analyses
was obtained from Cambridge Isotope Laboratories Inc. (Andover, MA, USA). Dimethyl
terephthalate (DMT), a certified reference material, was provided by the Division of Chem-
ical and Thermal Metrology (Inmetro, Rio de Janeiro, Brazil), under certification num-
ber DIMCI 1507/2019 (certified purity: 99.988 ± 0.060%). The reagents used in antioxi-
dant assays, including 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox),
2,2-diphenyl-1-picrylhydrazyl (DPPH• ), and 2,2′ -azino-bis(3-ethylbenzothiazoline-6-sulfonic
acid) and ammonium salt (ABTS•+ ), were obtained from Sigma-Aldrich (St. Louis, MO,
USA). Similarly, albumin, fructose and sodium azide used in the antiglycation assay
were sourced from Sigma-Aldrich (St. Louis, MO, USA). For the cytotoxic and antiviral
assay, Dulbecco’s Modified Eagle’s Medium (DMEM) and 3-(4,5-dimethylthiazol-2-yl)-2,5-
diphenyltetrazolium bromide (MTT) were obtained from Sigma-Aldrich (St. Louis, MO,
USA), while penicillin, streptomycin, non-essential amino acids, and fetal bovine serum
were sourced from Gibco Life Technologies (Carlsbad, CA, USA). The ZIKV rabbit anti-NS3
primary antibody was kindly provided by Professor Andres Merits [49]. Goat anti-rabbit
IgG Alexa Fluor 488 was sourced from Invitrogen (Waltham, MA, USA).

3.2. Plant Material

The leaves of E. punicifolia were collected during different months [August 2021
(dry period), December 2021 (transition period), and March 2022 (rainy period)] at the
Brazilian Agricultural Research Corporation—Embrapa Amazônia Ocidental—located
along Rodovia AM-010, Km 29 (2◦ 53′ 23′′ S 59◦ 58′ 26′′ W). Access to genetic heritage
was registered (A82BD35) in the National System of Management of Genetic Heritage
and Associated Traditional Knowledge (SisGen). From a plantation of 150 individuals,
15 trees were randomly selected, and leaves were gathered from various heights to ensure a
representative sample (11 leaves each from the lower, middle, and upper parts of the trees).
The collected plant material was dried at room temperature for 24 h, followed by 48 h in a
forced air circulation oven at 40 ◦ C. After drying, each sample was subjected to the cold
maceration process with liquid nitrogen, weighed, and then stored in a freezer at −80 ◦ C
until the extraction procedure.

3.3. Extraction Procedure

The extraction systems used were selected based on the methodology described by
Santos et al. (2020) [9]. For the extractions, 1.0 g of the sample mixture from each collection
was subjected, in triplicate, to four different extraction systems: [1: methanol (100%)—M;
2: ethanol (100%)—E; 3: ethanol (50%)/methanol (50%)—EM; and 4: methanol (60%)/ethanol
(20%)/water (20%)—MEW]. Each extraction was performed four times and sonicated in an
ultrasonic bath for 15 min, followed by centrifugation at 4000 rpm for 10 min (4226× g).
Molecules 2025, 30, 713 10 of 16

The supernatant was then separated and dried using nitrogen gas. Statistical analysis of
the extraction yields was conducted using Minitab 18.1, employing the analysis of variance
(ANOVA) with the Tukey’s test and a significance level of 95% [50].

3.4. Acquisition and Processing of NMR Data

Twenty milligrams (20.0 mg) of each E. punicifolia leaf extract was solubilized in
520 µL of DMSO-d6 , sonicated in an ultrasonic bath for 10 min, and then transferred to a
5 mm NMR tube. NMR spectra were acquired using a Bruker Avance IIIHD NMR spec-
trometer (Bruker, Billerica, MA, USA), operating at 11.7 T (500 MHz for 1 H) and equipped
with a 5 mm BBFO Plus SmartProbe™ with a Z-axis gradient. The pulse sequences used
were obtained from the Bruker database. The zgpr pulse sequence was used, with the
following acquisition parameters: time domain (TD) data points of 32k, spectral width
(SW) of 8 kHz, acquisition time (AQ) of 1.64 s, receiver gain (RG) of 90.5, number of scans
(NS) equal to 32, dummy scans of 2, FID resolution of 0.30 Hz, central frequency (O1) set to
1667.48 Hz, and suppression power (PLW9) of 8.6289e−005 . The P1 value was automatically
calculated for each sample using the pulsecal sn command. The D1 values for signals corre-
sponding to the aromatic compounds were calculated using Equation (1). The longitudinal
relaxation constant (T1) was determined using an inversion–recovery experiment (t1ir)
pulse sequence, and the highest T1 value was used to determine the D1 value (15 s) for the
sample acquisition.
D1 = 7 × T1 − AQ (1)

The dimethyl terephthalate (DMT) was prepared in triplicate at a concentration of

20.12 mM in DMSO-d6 (D, 99.9%) with TMS (0.05% v/v) as an internal reference standard
(0.00 ppm). For the quantitative 1 H NMR spectrum, the 90◦ pulse of DMT (10.65 µs)
was calculated for the signal at δ 8.10 (s, 4H) using the 90◦ pulse experiment (zg). The
determination of T1 was carried out using the t1ir1d experiment for the signal at δ 8.10.
After obtaining the T1 value, D1 (16.62 s) was estimated using Equation (1), for which the
acquisition time (AQ) was set to 1.64 s. Except for the P1 and D1 parameters, the same
acquisition parameters used for the quantitative spectra of the extracts were applied to the
acquisition of DMT.
Phase and baseline corrections of the spectra were performed manually using TopSpin
3.6.3 software. The chemical shift (in ppm) of the 1 H NMR spectra was referenced to the
methyl signal of tetramethylsilane at δH 0.00, and the coupling constants (J) were recorded
in Hz. HSQC and HMBC NMR experiments were conducted to verify the absence of signal
overlap with the signals of interest, with the 1 H-13 C correlations acquired using coupling
constants J (H, C—single bond) and J (H, C—long-range) of 145 and 8 Hz, respectively.
Signal integration was performed manually, and the quantification of phenolic compounds
using the PULCON method was carried out with the ERETIC2 (electronic reference to
access in vivo concentrations) tool in TopSpin 3.6.3 software [51,52].

3.5. Cell Culture

The Vero E6 cells (kidney tissue derived from a normal adult African green monkey,
ATCC E6/CRL-1586) were cultured in Dulbecco’s modified Eagle’s medium supplemented
with 100 U mL−1 penicillin, 100 mg mL−1 streptomycin, 1% (v/v) non-essential amino
acids, and 10% (v/v) fetal bovine serum at 37 ◦ C in a humidified 5% CO2 incubator.

3.6. Cell Viability Assay

Cell viability was measured via the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl
tetrazolium bromide] method. The Vero E6 cells were seeded in 96-well plates at a density
of 5 × 103 cells per well and incubated overnight at 37 ◦ C in a humidified 5% CO2 incubator.
Molecules 2025, 30, 713 11 of 16

The drug-containing medium at the concentrations of 50, 10, and 2.0 µg mL−1 was added to
the cell culture for 72 h at 37 ◦ C. Then, the medium was removed, and a solution containing
MTT at the final concentration of 1 mg mL−1 was added to each well and incubated for
30 min at 37 ◦ C in a humidified 5% CO2 incubator, after which media were replaced with
100 µL of DMSO to solubilize the formazan crystals. Absorbance was measured using the
optical density (OD) of each well at 560 nm, using a GloMax® microplate reader (Promega,
Madison, WI, USA). Cell viability was calculated according to the equation (T/C) × 100%,
where T and C represent the mean optical density of the treated group and vehicle control
group, respectively.

3.7. Antiviral Assay—ZIKV

A wild-type ZIKV isolate from a clinical sample of a patient in Brazil (ZIKVPE243 ) was
amplified employing infected Vero E6 cells in 75 cm² flask for 3 days [53]. Then, the viral
supernatant was collected and stored at −80 ◦ C. To determine viral titers, 5 × 103 Vero
E6 cells were seeded in each of the 96-well plates 24 h prior to the infection. Cells were
infected with 10-fold serial dilution of ZIKVPE243 and incubated for 72 h in a humidified 5%
CO2 incubator at 37 ◦ C. Following this, the cells were fixed with 4% formaldehyde, washed
with phosphate-buffered saline (PBS), and a blocking buffer (BB) was added containing
0.10% Triton X-100, 0.20% bovine albumin, and PBS for 30 min. An immunofluorescence
assay was performed as previously described [54]. In summary, the cells were incubated
with the ZIKV anti-NS3 primary antibody, followed by a second incubation with the goat
anti-rabbit IgG Alexa Fluor 488. Images were analyzed using EVOs Cell Imaging Systems
Fluorescence Microscopy (Thermo Fisher Scientific), and the foci of infection were counted
and measured as focus-forming units (FFUs mL−1 ) for viral titer determination.
To assess the antiviral activity of each extract, the Vero E6 cells were seeded at a
density of 5 × 103 cells per well into 96-well plates for 24 h and infected with ZIKVPE243
at a multiplicity of infection (MOI) of 0.01 FFU/cell in the presence of each compound
at the established non-cytotoxic concentration. After 72 h, the cells were fixed with 4%
formaldehyde, incubated for 30 min, washed with PBS, and the BB was added for the im-
munofluorescence assay for FFU determination. Viral replication was calculated according
to the equation (T/C) × 100%, where T and C represent the FFU mean of the treated group
and vehicle control group, respectively.
Data were analyzed for normal distribution to demonstrate the applicability of a
parametric or nonparametric tests. Subsequently, two-way ANOVA, using GraphPad
Prism 10.3.0 software, was employed to compare the treatment of each compound with
DMSO (0.1%) as a negative control, with significance set at p < 0.05 [55].
All the ZIKV infection assays were performed at a BSL-2 laboratory under the
authorization number CBQ: 163/02 and process SEI: 01.245.006267/2022–14 from the
CTNBio—National Technical Commission for Biosecurity from Brazil.

3.8. Determination of Antioxidant Potential

3.8.1. DPPH Radical Scavenging Capacity
The experiments were conducted following the methodology of Samaniego-Sánchez
et al. (2011) with adaptations by Mar et al. (2021) [56,57]. The free-radical scavenging
capacity of E. punicifolia leaf extracts was assessed using the DPPH• radical method. A
100 µM methanolic DPPH• solution was prepared. The samples were then prepared at a
concentration of 1.0 mg mL−1 and mixed with 1900 µL of the methanolic DPPH• solution.
Trolox, at a concentration from 100 to 2000, was used as a positive control. The mixture
was incubated in the dark at 25 ◦ C for 30 min. Absorbance was measured at 515 nm
using a microplate reader (Bio Tek Instruments Inc., Winooski, VT, USA). The antioxidant
Molecules 2025, 30, 713 12 of 16

capacity was quantified in Trolox equivalents, and the assay was performed in tripli-
cate. The relationship between absorbance and Trolox concentration was determined as
y = −0.0004x + 0.731, with an R2 value of 0.9944. All measurements were made in triplicate,
and the results were expressed in micromolar Trolox equivalents (µM Trolox mL−1 ).

3.8.2. ABTS Radical Cation Scavenging Capacity

The ABTS•+ -scavenging assay involves observing the color bleaching of the ABTS•+
solution in the presence of antioxidant extracts at a concentration of 1.0 mg mL−1 .
The methodology of Samaniego-Sánchez et al. (2011) was utilized, with adaptations
(Mar et al., 2021) [56,57]. After a 6 min reaction between the sample and the radical at
a 1:10 ratio, absorbances were measured at 750 nm using a microplate reader (Bio Tek
Instruments Inc., Winooski, VT, USA). Trolox was used to construct the standard curve
(y = 0.0003x + 0.7473, R2 = 0.999), and the results were expressed as mean ± standard
deviation (n = 3) of the micromolar Trolox equivalents (µM Trolox mL−1 ).

3.9. Antiglycation Activity: Non-Oxidative Pathway

The ability to inhibit the formation of advanced-glycation end-products (AGEs) was
evaluated according to the method of Kiho et al. (2004), with slight modifications [58]. The
reaction was carried out in triplicate using the following concentrations: 10.0 mg mL−1
albumin (BSA), 30 mM fructose, and 1.00 mg mL−1 of the sample (dissolved in DMSO).
The fructose and BSA solutions were prepared in a phosphate buffer (0.20 M, pH 7.4) with
3.0 mM sodium azide as an antimicrobial agent. The 300 µL of the total reaction mixture
consisted of BSA (135 µL), fructose (135 µL), and DMSO or sample (30 µL). The mixture
was incubated at 37 ◦ C for 48 h under sterile conditions and in the dark. After incubation,
each sample was analyzed in a microplate reader for fluorescence intensity (emission
λ 330 nm and excitation λ 420 nm). Aminoguanidine was used as a standard, and DMSO
served as a negative control. The percentage inhibition was calculated using Equation (2),
and the results are expressed as mean % inhibition ± standard deviation (n = 3).

% inhibition = 100 − [Fluora/p/FLuorC] × 100 (2)

where: Fluora/p = (White fluorescence − Sample fluorescence); FLuorC = (White fluores-

cence − Control fluorescence).

3.10. Canonical Correlation Analysis (CCA)

CCA was conducted using Pearson’s correlation coefficient as a correlation index
between the chemical composition and the bioactivities of the extracts obtained during the
dry and rainy periods. The concentrations of the compounds determined using 1 H NMR,
along with the antioxidant potential and AGE inhibition values, were used as variables.
Pearson correlation coefficients were calculated using GraphPad Prism 10.3.0 software,
with a 95% confidence interval and significance set at p < 0.05 (two-tailed) [55].

4. Conclusions
This investigation revealed that the extraction system and seasonality significantly
influence the quantitative chemical profile and the antioxidant, antiglycation, and antiviral
activities of Eugenia punicifolia leaf extracts. The MEW (methanol/ethanol/water) system
proved to be the most efficient for extracting bioactive compounds, showing strong an-
tioxidant and antiglycation potentials, especially in samples collected during the rainy
season. The use of quantitative NMR and canonical correlation analysis (CCA) allowed
for the identification and quantification of key phenolic compounds, including gallic acid,
catechin, quercetin, and myricetin, which were linked to the observed pharmacological
Molecules 2025, 30, 713 13 of 16

effects. These compounds can serve as chemical markers for tracking the antioxidant,
antiglycation, and antiviral activities of E. punicifolia leaf extracts. Overall, this research
highlights the importance of choosing the appropriate extraction methods and season to
maximize the pharmacological potential of plant-based extracts.

Supplementary Materials: The following supporting information can be downloaded at

https://www.mdpi.com/article/10.3390/molecules30030713/s1: Figure S1. Effect of extract of
Eugenia punicifolia leaves on viability of Vero E6 cells. Vero E6 cells were treated with each compound
at the highest non-cytotoxic concentration. After 72 h, cell viability was measured via the MTT assay.
Viability was measured by absorbance (560 ηM). DMSO was used as the untreated control. Mean
values of two independent experiments, each measured in triplicate including the standard error of
the mean, are shown. p values < 0.05 were considered significant. (**) p < 0.01, (***) p < 0.001, and
(****) p < 0.0001, Figure S2. 1 H NMR spectrum (500 MHz, DMSO-d6 ) of MEW extract of Eugenia
punicifolia leaves collected during the dry season (−1.00 to 10.00 ppm), Figure S3. HSQC spectrum
(500 MHz, DMSO-d6 ) of MEW extract of Eugenia punicifolia leaves collected during the dry season
(range magnification of 1 H: −0.50 to 8.30 ppm—13C: −3.0 to 158.0 ppm), Figure S4. HSQC spectrum
(1 H: 500 MHz, 13 C: 125 MHz DMSO-d6 ) of MEW extract of Eugenia punicifolia leaves collected during
the dry season (range magnification of 1 H: 5.50 to 7.80 ppm—13 C: 96.0 to 128.0 ppm). Signals corre-
sponding to gallic acid (1: δ 6.95—δ 108.6), quercetin (2: δ 7.30—δ 115.5), myricetin (3: δ 7.01—δ 108.7),
catechin (4: δ 5.93—δ 95.4) and epigallocatechin (5: δ 5.89—δ 95.1)], Figure S5. HMBC spectrum
(1 H: 500 MHz, 13 C: 125 MHz DMSO-d6 ) of MEW extract of Eugenia punicifolia leaves collected during
the dry season (range magnification of 1 H: −0.50 to 8.50 ppm—13C: −4.7 to 193.3 ppm), Figure S6.
HMBC spectrum (1 H: 500 MHz, 13 C: 125 MHz DMSO-d6 ) of MEW extract of Eugenia punicifolia
leaves collected during the dry season (range magnification of 1 H: 5.55 to 7.40 ppm—13 C: 50.7
to 180.2 ppm), Figure S7. 1 H NMR spectrum (500 MHz, DMSO-d6 ) of extracts of Eugenia punici-
folia leaves collected during the dry season (−1.00 to 10.00 ppm), Figure S8. 1 H NMR spectrum
(500 MHz, DMSO-d6 —range magnification from 8.00 to 5.50 ppm) of extracts of Eugenia punicifolia
leaves collected during the dry season. Signals corresponding to gallic acid (1: δ 6.95), quercetin
(2: δ 7.30), myricetin (3: δ 7.01), catechin (4: δ 5.93) and epigallocatechin (5: δ 5.89)]. Extract acronyms:
MEW—methanol/ethanol/water; M—methanol; EM—ethanol/methanol; and E—ethanol, Figure S9.
1 H NMR spectrum (500 MHz, DMSO-d ) of extracts of Eugenia punicifolia leaves collected dur-
6
ing the transition season (−1.00 to 10.00 ppm region), Figure S10. 1 H NMR spectrum (500 MHz,
DMSO-d6 —range magnification from 8.00 to 5.50 ppm) of extracts of Eugenia punicifolia leaves col-
lected during the transition season. Signals corresponding to gallic acid (1: δ 6.95), quercetin (2: δ
7.30), myricetin (3: δ 7.01), catechin (4: δ 5.93) and epigallocatechin (5: δ 5.89)]. Extract acronyms:
MEW—methanol/ethanol/water; M—methanol; EM—ethanol/methanol; and E—ethanol,
Figure S11. 1 H NMR spectrum (500 MHz, DMSO-d6 ) of extracts of Eugenia punicifolia leaves col-
lected during the rainy season (−1.00 to 10.00 ppm), Figure S12. 1 H NMR spectrum (500 MHz,
DMSO-d6 —range magnification from 8.00 to 5.50 ppm) of extracts of Eugenia punicifolia collected
during the transition season. Signals corresponding to gallic acid (1: δ 6.95), quercetin (2: δ
7.30), myricetin (3: δ 7.01), catechin (4: δ 5.93) and epigallocatechin (5: δ 5.89). Extract acronyms:
MEW—methanol/ethanol/water; M—methanol; EM—ethanol/methanol; and E—ethanol, Table S1.
Pearson correlation coefficient between the concentration determined by 1 H NMR and the scavenging
capacity of the DPPH radical, the ABTS radical cation and inhibition of AGE formation. 1—gallic
acid, 2—epigallocatechin, 3—catechin, 4—quercetin and 5—myricetin.

Author Contributions: Conceptualization: K.O.G.N., A.D.C.S. and M.B.M.; methodology, identifi-

cation and collection of botanical material: F.C.M.C.; NMR analysis: K.O.G.N., S.O.S. and M.S.C.;
antiglycation activity: L.D.R.A. and E.S.L.; antioxidant potential: J.M.M., J.A.B. and E.A.S.; cell
viability assay and antiviral assay: N.M.C., G.A.A. and A.C.G.J.; statistical analysis: K.O.G.N.;
writing—review and editing: K.O.G.N., A.D.C.S. and M.B.M. All authors have read and agreed to the
published version of the manuscript.
Molecules 2025, 30, 713 14 of 16

Funding: This research has also provided by FAPEMIG (Fundação de Pesquisa do Estado de Minas
Gerais, APQ-01487-22, APQ-04686-22), CAPES Prevention and Combat of Outbreaks, Endemics, Epi-
demics and Pandemics (88887.506792/2020-00) under Finance Code 001, CNPq (Conselho Nacional
de Ciência e Tecnologia, 409187/2023-2 and 421935/2023-5), and Fundação de Amparo à Pesquisa do
Estado do Amazonas—FAPEAM (Edital number 010/2021—CT&I Áreas Prioritárias).

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Data Availability Statement: The primary data and contributions of this study are provided
within the article and supplementary materials. For additional information, please contact the
corresponding author(s).

Acknowledgments: The authors would like to thank CAPES, Financiadora de Estudos de Projetos e
Programa—FINEP, FAPEMIG, and FAPEAM. A.C.G.J. received a CNPq productivity fellowship.

Conflicts of Interest: The authors declare that there are no conflicts of interest.

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