plants

Article
The Influence of Phytosociological Cultivation and Fertilization
on Polyphenolic Content of Menthae and Melissae folium and
Evaluation of Antioxidant Properties through In Vitro and In
Silico Methods
Emanuela Alice Lut, ă 1, *,† , Andrei Bit, ă 2,† , Alina Moros, an 3, * , Dan Eduard Mihaiescu 3 , Manuela Ghica 1,† ,
Dragos, Paul Mihai 1, *,† , Octavian Tudorel Olaru 1, *,† , Teodora Deculescu-Ionit, ă 1 , Ligia Elena Dut, u 1 ,
Maria Lidia Popescu 1 , Liliana Costea 1 , George Mihai Nitulescu 1 , Dumitru Lupuliasa 1,‡ , Rica Boscencu 1,‡
and Cerasela Elena Gîrd 1,‡

1 Faculty of Pharmacy, University of Medicine and Pharmacy “Carol Davila”, Traian Vuia 6,
020956 Bucharest, Romania
2 Department of Pharmacognosy & Phytotherapy, Faculty of Pharmacy, University of Medicine and Pharmacy
of Craiova, Petru Rares, 2, 200349 Craiova, Romania
3 Department of Organic Chemistry “Costin Nenit, escu”, Faculty of Chemical Engineering and Biotechnologies,
University of Politehnica, Gheorghe Polizu 1-7, 011061 Bucharest, Romania
* Correspondence: emanuela.luta@drd.umfcd.ro (E.A.L.); alina.morosan@upb.ro (A.M.);
dragos_mihai@umfcd.ro (D.P.M.); octavian.olaru@umfcd.ro (O.T.O.)
Citation: Lut, ă, E.A.; Bit, ă, A.; † These authors contributed equally to this work.
‡ These authors contributed equally to this work.
Moros, an, A.; Mihaiescu, D.E.; Ghica,
M.; Mihai, D.P.; Olaru, O.T.;
Deculescu-Ionit, ă, T.; Dut, u, L.E.; Abstract: Since medicinal plants are widely used in treating various diseases, phytoconstituents
Popescu, M.L.; et al. The Influence of enrichment strategies are of high interest for plant growers. First of all, we investigated the im-
Phytosociological Cultivation and pact of phytosociological cultivation on polyphenolic content (total flavonoids—TFL, and total
Fertilization on Polyphenolic Content polyphenols—TPC) of peppermint (Mentha piperita L.) and lemon balm (Melissa officinalis L.) leaves,
of Menthae and Melissae folium and using spectrophotometric methods. Secondly, the influence of chemical (NPK) and organic (BIO)
Evaluation of Antioxidant Properties fertilization on polyphenolic content and plant material quality was also assessed. Dry extracts
through In Vitro and In Silico
were obtained from harvested leaves using hydroethanolic extraction solvents for further qualitative
Methods. Plants 2022, 11, 2398.
and quantitative assessment of phytoconstituents by FT-ICR MS and UHPLC-MS. Furthermore, the
https://doi.org/10.3390/
antioxidant activity of leaf extracts was determined in vitro using DPPH, ABTS and FRAP meth-
plants11182398
ods. Molecular docking simulations were employed to further evaluate the antioxidant potential
Academic Editor: Ahmed A. of obtained extracts, predicting the interactions of identified phytochemicals with sirtuins. The
Hussein concentration of polyphenols was higher in the plant material harvested from the phytosociological
Received: 24 August 2022 culture. Moreover, the use of BIO fertilizer led to the biosynthesis of a higher content of polyphenols.
Accepted: 13 September 2022 Higher amounts of phytochemicals, such as caffeic acid, were determined in extracts obtained from
Published: 14 September 2022 phytosociological crops. The antioxidant activity was dependent on polyphenols concentration,
more potent inhibition values being observed for the extracts obtained from the phytosociological
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
batches. Molecular docking studies and MM/PBSA calculations revealed that the obtained extracts
published maps and institutional affil- have the potential to directly activate sirtuins 1, 5 and 6 through several polyphenolic compounds,
iations. such as rosmarinic acid, thus complementing the free radical scavenging activity with the potential
stimulation of endogenous antioxidant defense mechanisms. In conclusion, growing medicinal plants
in phytosociological cultures treated with biofertilizers can have a positive impact on plant material
quality, concentration in active constituents and biological activity.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland. Keywords: Mentha piperita L. leaves extract; Melissa officinalis L. leaves extract; phytosociology;
This article is an open access article
polyphenolic content; FT-ICR MS; UHPLC-MS; antioxidant activity; molecular docking; sirtuins
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).

Plants 2022, 11, 2398. https://doi.org/10.3390/plants11182398 https://www.mdpi.com/journal/plants

Plants 2022, 11, 2398 2 of 26

1. Introduction
The use of medicinal plants in various types of ailments has attracted many research
efforts into their cultivation. Enrichment in active principles, generation of a larger mass
of quality plant products can become major concerns for medicinal plant growers. In this
context, studying combinations of medicinal plants belonging to the same family or to
different classes may constitute new and growing research directions. Rotational cultivation
or intercropping of medicinal plants with various food species may be another starting
point for various research projects aimed at enriching plant products with biologically
active compounds. Rotational cropping has already been practiced for a long time and on a
large scale in agriculture. Intercropping refers to the simultaneous cultivation of two or
more species in the same area or plot during a growing season. In an intercropping study
of mint and Vicia faba L., it was found that a higher amount of volatile oil was produced
in mint, and that the dominant compounds, menthol and menthone, did not positively
influence the amount of generated biomass [1]. In another intercrop of mint and soybean,
a positive influence on the quality of mint volatile oil was observed, with menthol being
produced in higher amounts [2]. The main purpose of these types of experimental crops
is to limit the aggressiveness of external factors, such as plants (weeds) or animal (insects
etc.) pests, applying possible quantifiable treatments, in order to obtain a higher plant
mass production compared to monoculture systems. However, when fennel and dill were
intercropped, a large amount of biomass was provided only by Anethum graveolens L., also
acting as the dominant species [3].
Based on all these aspects, the paper presents the initiation of a phytosociology study,
in which the aim was to cultivate two medicinal species with extensive use in phytother-
apy, Mentha piperita L. (mint) and Melissa officinalis L. (melissa, lemon balm), in common
(phytosociological) crops. One of the scopes of the present study started from a simple
premise: the possibility that there might be either positive or negative differences in the
biosynthesis of certain active chemical constituents or the supply of plant mass for different
types of medicinal species cultivated in common cultures
Mentha piperita L. (mint) is a well-known species in eastern and northern Europe,
cultivated continuously at a worldwide scale. Mint leaves (Menthae folium) are widely
used in phytotherapy for their digestive tonic (volatile oil and bitter principles), choleretic-
cholagogue and antispasmodic (flavones, polymethoxylated flavones, volatile oil esters,
caffeic acid, chlorogenic acid), antidiarrheal (tannin and volatile oil), anti-infectious (tannin,
volatile oil), antiemetic (menthol in the volatile oil, which causes slight anesthesia of the
gastric mucosa), antipruritic (menthol in the volatile oil), mildly sedative (esters in the
volatile oil), antifungal, antiviral (active on herpes virus, due to volatile oil, rosmarinic
acid), analgesic (volatile oil) and antioxidant (polyphenols) activities [4–10].
Melissa officinalis L. (melissa, lemon balm), a species of the Lamiaceae family such as
mint, is associated in phytotherapy for its sedative, antispasmodic (through aldehydes
and esters in the volatile oil), choleretic-cholagogue (through caffeic acid, chlorogenic acid,
sea principles), antiherpetic, antimicrobial (through rosmarinic acid and aldehydes in the
volatile oil), immunomodulating (through polyphenolic derivatives and volatile oil) and
antioxidative (through polyphenols) activities [11–14].
The main scope of the present study was to assess whether it is possible to generate
compatible batches of medicinal plants that grow together and produce higher amounts of
polyphenolic derivatives and plant mass. More specifically, the objectives of the study were
as follows: to monitor mint and melissa crops from common batches and to compare with
single-component batches in terms of variation in polyphenol content (flavones and total
polyphenols); to compare the polyphenol content in plant products from batches supple-
mented with biofertilizers and chemical fertilizers; to obtain dry extracts in which the aim
was to quantify by spectrophotometric and HPLC methods the polyphenolic derivatives;
and to evaluate their antioxidant action using both in vitro and in silico methods. The
in vitro methodology consisted in the assessment of the direct antioxidant activity using
free radical scavenging assays. The in silico studies were used to evaluate the potential
Plants 2022, 11, 2398 3 of 26

of identified phytochemicals to stimulate the endogenous antioxidant defenses through

indirect mechanisms of action, such as stimulating the enzymatic activities of sirtuins.
Sirtuins are a class of nicotinamide-adenine dinucleotide (NAD)-dependent deacety-
lases which were shown to play important roles in oxidative stress, inflammation and
ageing. There are seven known sirtuin isoforms (SIRT1-7) that are localized either in
the cytoplasm (SIRT2), mitochondria (SIRT3, SIRT4, SIRT5) or nucleus (SIRT1, SIRT6,
SIRT7) [15,16]. Pharmacological activation of sirtuins can have beneficial effects in ox-
idative stress-related disorders, and several phytochemical compounds were found as
up-regulators, such as curcumin, resveratrol, fisetin and quercetin [17–20]. Therefore, in
this present study we also aimed to investigate the potential stimulatory activity of the de-
tected polyphenols on three sirtuin isoforms (SIRT1, SIRT5 and SIRT6) by using molecular
docking simulations.

2. Result
2.1. Quantitative Chemical Analysis of Plant Material from Single and Phytosociological Crops
The results obtained from the quantitative chemical determinations are presented in
Table 1.

Table 1. Quantitative analysis of polyphenols from plant material.

TFL (mg/g Eq TPC (mg/g Eq Expressed

Plant Sample Solvent
Expressed in Rutin) in Tannic Acid)
MM 50% Alcohol 10.11 ± 2.526 91.80 ± 14.828
MF 50% Alcohol 25.87 ± 5.766 101.43 ± 19.329
MLM 70% Alcohol 16.12 ± 2.692 40.90 ± 10.775
MLF 70% Alcohol 22.71 ± 5.160 65.84 ± 28.841
Total flavonoids content (TFL), total phenolic content (TPC). MM—peppermint, control crop; MF—peppermint
phytosociological (common) crop; MLM—lemon balm control crop; MLF—lemon balm control (common) crop.
Results were expressed as Mean ± SD (n = 5).

As expected, from a quantitative, chemical point of view, the plant products from the
four batches had variable contents in secondary metabolites. It was found that the amount
of polyphenolic derivatives in the phytosociological crops is significantly higher than in the
control crops. For mint, the concentration of TFL is twice as high in the phytosociological
batch (25.87 ± 5.766 mg/g) compared to the control batch (10.11 ± 2.526 mg/g) and TPC
are 1.10 times higher in the phytosociological group (101.43 ± 19.329 mg/g). Lemon balm
plant material coming from the phytosociological crop contained 1.4 times more flavones
and 1.6 times more TPC when compared to the control batch. Statistically, as can be seen in
detail in relation to the level of significance in the boxplot graphs (Figures S43 and S44),
it can be observed that simple main effects analysis indicated that the common crop is
statistically different from control crop (p = 0.0002). Post hoc analysis indicated that there
was a visible difference in the case of TPC only for lemon balm.

2.2. The Influence of Fertilization on the Quality of Soil and Plant Raw Materials
Productive agricultural soils were used for the growth of the studied cultures. Unfortu-
nately, we did not possess previous data on soil quality for comparison with our results. In
the first stage we performed a soil analysis in order to choose the optimal type of fertilizer.
After applying both chemical and the biological fertilizers, we established two new batches
of mint and lemon balm on the two types of fertilized soils. The last stage consisted in
collecting the leaves from both species and assessing the influence of fertilization on micro-
and macroelements content. The composition of the two fertilized soils was also analyzed.
All the obtained data are presented in Table 2.
In general, most cultivated plants prefer neutral or weakly alkaline soils (pH = 6.3–7.5).
The NPK-fertilized soil has a slightly lower alkalinity, its pH decreasing from 8.06 in the
initial crop to 7.38, possibly due to slightly acidic constituents. In the crop treated with
organic fertilizer, the alkalinity is almost the same as in the control crop. However, a slight
Plants 2022, 11, 2398 4 of 26

increase in humus concentration was observed for both batches, which can be explained
by the compositions of the two types of fertilizers. Nonetheless, there are no significant
differences between the fertilized batches regarding this aspect.

Table 2. Quantitative analysis of soils and plant materials.

Identification ID ID
ID 1055 MF ML F M NPK ML NPK M Bio ML Bio
Probe 103-21 1054
pH 8.06 7.38 8.05 - - - - - -
HUM [mg/kg] 28.10 36.70 36.10 - - - - - -
Res. Cond. [mg/kg] 400.00 1780.00 880.00 - - - - - -
N [mg/kg] 1.98 2.73 2.41 37.00 17.60 45.90 26.30 37.60 25.00
P [mg/kg] 403.00 1118.00 660.00 3.60 4.50 4.80 3.60 4.30 4.20
K [mg/kg] 359.00 752.00 464.00 17.80 25.90 21.20 24.00 18.70 24.10
Ca [mg/kg] - - - 21.90 12.10 21.40 12.50 18.30 12.20
Zn [mg/kg] 3.60 7.30 5.90 222.00 360.00 264.00 212.00 219.00 314.00
Cu [mg/kg] 5.90 6.40 5.50 111.00 134.00 111.00 121.00 108.00 130.00
Fe [mg/kg] 12.00 11.20 9.00 1760.00 4720.00 3320.00 2690.00 3840.00 4540.00
Mn [mg/kg] 10.05 15.90 13.90 350.00 254.00 402.00 196.00 380.00 259.00
ID 103-21—control soil sample, ID 1054—NPK fertilized soil sample, ID 1055—BIO fertilized soil sample; M F—
mint sample, control crop, unfertilized soil; ML F—lemon balm sample, control crop, unfertilized soil; M NPK—
mint sample, NPK fertilized soil; ML NPK—lemon balm sample, NPK fertilized soil; M Bio—mint sample, BIO
fertilized soil; ML Bio—lemon balm sample, BIO fertilized soil, HUM—humus, Res. Cond.—determination of
electrical conductivity and estimation of total soluble salt content, N—nitrogen, P—phosphorus, K—potassium,
Ca—calcium, Zn—zinc, Fe—iron, Mn—manganese.

We found that microelements had variable concentrations in the analyzed samples, the
use of fertilizers leading to the increase in trace elements. The total nitrogen concentration
is higher in the M NPK crop compared to the mint organic crop. Total phosphorus was
in approximately equal amounts in M Bio and ML Bio and was higher in the M NPK.
Potassium concentration decreased in the fertilized batches, and the highest amounts were
found in the ML F batch. The concentration in calcium in the M NPK group was almost
identical with the values measured in the M F group; however, it was found to be lower in
the M Bio group. Moreover, zinc content increased in the NPK-fertilized crop by 2-fold,
and in the organic fertilized crop by 1.6-fold. An interesting decrease in iron concentration
was noticed for the organic fertilized crop (0.7-fold lower than in the control batch). In the
case of manganese, its concentration increased by 1.5-fold in the NPK-fertilized crop. All
these fluctuations in soil quality and trace element concentrations are due to the different
chemical composition of the two fertilizers.
An increase in the majority of values for assessed parameters can be easily observed
Plants 2022, 11, 2398 5 of
for the plots coming from NPK-fertilized soils. It should be noted that plant species grown
in soil with NPK fertilizer are also more developed (Figure 1).

(a) (b)

Figure 1. (a) MML Figure 1. (a) NPK-fertilized

crops from MML crops fromsoil;
NPK-fertilized soil; (b)
(b) MML crops fromMML crops fromsoil.
bio-fertilized bio-fertilized soil.

2.3. The Influence of Fertilizers on the Biosynthesis of Polyphenols

The results of quantitative chemical determinations on plant products harvest
from fertilized soils are shown in Table 3 and were compared with control crops (fro
unfertilized soil).

Table 3. Quantitative analysis of plant products harvested from fertilized crops.

Plants 2022, 11, 2398 5 of 26

2.3. The Influence of Fertilizers on the Biosynthesis of Polyphenols

The results of quantitative chemical determinations on plant products harvested
from fertilized soils are shown in Table 3 and were compared with control crops (from
unfertilized soil).

Table 3. Quantitative analysis of plant products harvested from fertilized crops.

TFL (mg/g Eq TPC (mg/g Eq Expressed

Plant Extract Solvent
Expressed in Rutin) in Tannic Acid)
MF 50% Alcohol 25.87 ± 5.766 101.43 ± 19.329
M NPK 50% Alcohol 22.71 ± 5.476 104.17 ± 21.563
M Bio 50% Alcohol 35.38 ± 6.649 120.09 ± 38.467
ML F 70% Alcohol 22.71 ± 5.160 65.84 ± 28.841
ML NPK 70% Alcohol 23.51 ± 6.588 70.26 ± 27.772
ML Bio 70% Alcohol 40.03 ± 5.417 83.41 ± 24.644
M F and ML F—mint and lemon balm from unfertilized soil; M NPK and ML NPK—mint and lemon balm from
fertilized common crop obtained with chemical fertilizer; M Bio and ML Bio—mint and lemon balm from fertilized
common crop obtained with biological fertilizer.

Some differences were observed in the content of active principles depending on

the type of used fertilizer. In the case of the chemical fertilizer (NPK), there was a slight
increase in the concentration of the three types of active principles determined in mint
and lemon balm. Moreover, an interesting observation was the significant increase in
concentrations in the batch grown with organic fertilizer. In mint crop, the concentration in
flavones increases almost 1.3-fold compared to the NPK batch, and for lemon balm, the
concentration of flavones almost doubled, while there was a notable increase for the other
active principles. Compared to the plots grown without fertilizers, the use of both chemical
and organic fertilization lead to a higher production of polyphenolic compounds. Although
the medicinal species from NPK-fertilized soil were more developed, the concentrations
of active ingredients were actually lower. Statistical analysis showed that there were
differences between sample crops only for lemon balm (Figures S45 and S46). Post hoc tests
revealed only for lemon balm that the bio crop is significantly different from the common
crop (p = 0.031) and the NPK crop (p = 0.014), but there were no significant differences
between the common and NPK crops (p > 0.05).

2.4. Phytochemical Analyses of Dry Plant Extracts

The results obtained from spectrophotometric determinations on plant extracts ob-
tained from the phytosociological and control crops are presented in Table 4. It should be
noted that the dried extracts were powdery and homogeneous, while the color and odor
were characteristic to the plant products from which they were obtained.

Table 4. Quantitative analysis of polyphenols in plant extracts.

Plant
TFL (mg/g Eq Expressed in Rutin) TPC (mg/g Eq Expressed in Tannic Acid)
Extract
MM E 54.70 ± 10.995 327.46 ± 3.003
MF E 86.78 ± 10.996 411.73 ± 13.696
MLM E 65.38 ± 15.772 333.67 ± 34.451
MLF E 78.74 ± 8.055 574.54 ± 45.203
Total flavonoids content (TFL), total phenolic content (TPC). Results were expressed as Mean ± SD (n = 5).
MM E—peppermint extract, control crop; MF E—peppermint extract, phytosociological (common) crop; MLM
E—lemon balm extract, control crop. MLF E—lemon balm extract, phytosociological (common) crop.

The analyzed results revealed that the dry extracts were enriched in polyphenolic
compounds and concentrations varied within wide limits. Interestingly, phytosociological
batches showed higher contents than those observed for controls. In mint, for instance, the
concentration in flavones was 1.5-fold higher in the extract obtained from the plant product
grown in the common batch and the total polyphenols were 1.2-fold higher in comparison
Plants 2022, 11, 2398 6 of 26

with the control batches. In lemon balm, the total polyphenol concentration is 1.7-fold
higher in the phytosociological crop.

2.5. FT-ICR MS (Fourier-Transform Ion–Cyclotron-Resonance High-Resolution Mass

Spectrometer)
Data obtained from FT-ICR MS, ESI+ and ESI− analyses are presented in Table 5.
The recorded spectra for ESI+, ESI− and the rest of the obtained spectra can be found in
Supplementary Materials (Figures S1–S42). It can be noted that, depending on the type of
ionization, there was a slight shift in atomic masses.

Table 5. Polyphenols found in sample extracts identified by FT–ICR MS.

Sample m/z MM E MF E MLM E MLF E

Name ESI+ ESI− ESI+ ESI− ESI+ ESI− ESI+ ESI− ESI+ ESI−
PRO - 153.02 - + - + - + - +
RUT 611.16 609.15 - + - + + + + +
CAF 181.05 179.03 + + + + + + + +
CHL 355.10 353.09 + + + + + + + +
LUT 287.06 285.04 + + + + + + + +
KAE 287.06 285.04 + + + + + + + +
ROS 361.09 359.08 + + + + + + + +
QUE 303.05 301.04 + + + + + + + +
ISO 465.10 463.09 + + + + + + + +
FER 195.07 193.05 + + + + + + + +
COU 165.05 163.04 - + - + + + + +
PRO—Protocatechuic acid, RUT—Rutin, CAF—Caffeic acid, CHL—Chlorogenic acid, LUT—Luteolin, KAE—
Kaempferol, ROS—Rosmarinic acid, QUE—Quercetin, ISO—Isoquercitrin, FER—Ferulic acid, COU—p-Coumaric
acid, m/z—atomic mass; MM E—peppermint extract, control crop; MF E—peppermint extract, phytosociological
(common) crop; MLM E—lemon balm extract, control crop; MLF E—lemon balm extract, phytosociological
(common) crop.

By this method, polyphenolic compounds were identified in plant extracts. In conse-

quence, negative ionization allowed the identification of a wider spectrum of polyphenolic
compounds in all types of analyzed crop extracts. Through positive ionization, protocate-
chuic acid could not be detected in any type of extract, while rutin and p-coumaric acid
were detected only in extracts obtained from lemon balm.
Mass spectra for polyphenolic compounds such as caffeic acid from mint and lemon
balm samples are presented in the Supplementary Materials (Figures S3, S11, S21 and S31).

2.6. UHPLC-MS (Ultra-High Performance Liquid Chromatography-MS)

Results after performing chromatographic analysis of the polyphenolic derivatives
from the four extract types are presented in Table 6, and the representative chromatograms
for each type of extract are shown in Figure 2.

Table 6. Polyphenol concentrations found in extracts (µg compound/g extract) identified by

UHPLC-MS quantification.

Sample Name MM E MF E MLM E MLF E

PRO [µg/g] 57.13 ± 1.883 48.62 ± 2.275 78.82 ± 1.910 98.54 ± 1.985
RUT [µg/g] 27.36 ± 2.117 68.00 ± 2.058 28.74 ± 2.256 205.82 ± 1.309
CAF [µg/g] 321.44 ± 1.727 345.45 ± 2.221 84.15 ± 2.146 1296.55 ± 1.911
CHL [µg/g] 56.09 ± 1.911 75.42 ± 2.385 73.99 ± 1.995 397.91 ± 2.237
LUT [µg/g] 99.68 ± 2.225 87.03 ± 1.652 121.19 ± 1.723 547.50 ± 1.866
KAE [µg/g] M 0.94 ± 0.148 1.22 ± 0.180 3.13 ± 0.689
ROS [µg/g] 43.95 ± 2.145 51.02 ± 2.080 48.59 ± 2.143 64.31 ± 1.750
QUE [µg/g] 5.93 ± 1.205 116.38 ± 2.100 4.62 ± 0.7605 76.84 ± 1.722
 2.6. UHPLC-MS (Ultra-High Performance Liquid Chromatography-MS)
Results after performing chromatographic analysis of the polyphenolic derivatives
from the four extract types are presented in Table 6, and the representative chromato-
Plants 2022, 11, 2398 7 of 26
grams for each type of extract are shown in Figure 2.

Table 6. Polyphenol concentrations found in extracts (μg compound/g extract) identified by

Table 6. Cont.
UHPLC-MS quantification.
Sample Name MM E MF E MLM E MLF E
Sample Name MM E MF E MLM E MLF E
ISO [µg/g] 176.48 ± 2.355 170.67 ± 2.165 170.67 ± 4.455 270.91 ± 2.108
PRO [μg/g]
FER [µg/g] 57.13
M ± 1.883 48.62
M ± 2.275 78.82
M ± 1.910 98.54
M ± 1.985
RUT[µg/g]
COU [μg/g] 28.8127.36 ± 2.11720.7868.00
± 1.888 ± 2.058 10.3228.74
± 1.722 ± 2.256 54.64205.82
± 1.624 ± 1.641± 1.309
CAF [μg/g]
PRO—Protocatechuic acid, 321.44 ± 1.727 345.45 ± 2.221 84.15 ± 2.146 1296.55
RUT—Rutin, CAF—Caffeic acid, CHL—Chlorogenic acid, LUT—Luteolin, ± 1.911
KAE—
Kaempferol, ROS—Rosmarinic acid, QUE—Quercetin, ISO—Isoquercitrin, FER—Ferulic acid, COU—p-Coumaric
acid, CHL [μg/g]MM E—peppermint
M—missing; 56.09 ± extract,
1.911 control
75.42 ± 2.385
crop; 73.99 ± extract,
MF E—peppermint 1.995 phytosociological
397.91 ± 2.237
(common)
LUTcrop; MLM E—lemon
[μg/g] balm±extract,
99.68 2.225control crop;± MLF
87.03 E—lemon
1.652 balm±extract,
121.19 1.723 phytosociological
547.50 ± 1.866
(common) crop, results were expressed as Mean ± SD (n = 3).
KAE [μg/g] M 0.94 ± 0.148 1.22 ± 0.180 3.13 ± 0.689
ROS [μg/g]
The quantitatively 43.95 ± 2.145
determined 51.02 ± compounds
polyphenolic 2.080 48.59 ± 2.143
varied 64.31limits
within broad ± 1.750
depending on the type of extract
QUE [μg/g] used in the
5.93 ± 1.205 analysis.
116.38 Although
± 2.100 4.62ferulic acid was76.84
± 0.7605 identified
± 1.722
by FT–ICR, the phytochemical
ISO [μg/g] 176.48could not be170.67
± 2.355 further±quantified by this±method,
2.165 170.67 4.455 its270.91
concentra-
± 2.108
tion being possibly below the detection limit. Higher concentrations of protocatechuic acid
FER [μg/g] M M M M
were found in the lemon balm extracts compared to mint extracts, caffeic acid concentration
wasCOU [μg/g]
15 times higher in the 28.81 ± 1.888
melissa extract20.78 ± 1.722
obtained from the10.32 ± 1.624
phytosociological 54.64
crop± 1.641
in
PRO—Protocatechuic
comparison with the acid, RUT—Rutin,
control; CAF—Caffeic
the concentration of acid, CHL—Chlorogenic
quercetin acid, LUT—Luteolin,
in the mint extract obtained
KAE—Kaempferol,
from the phytosociological batch was almost 20 times higher in comparison withFER—Ferulic
ROS—Rosmarinic acid, QUE—Quercetin, ISO—Isoquercitrin, the control acid,
COU—p-Coumaric
crop; kaempferolacid,
wasM—missing; MM
not quantified in E—peppermint
the mint extractextract, control
obtained fromcrop; MF E—peppermint
the control crop, and ex-
tract,
in phytosociological
all other extracts (common) crop; MLM
the concentration wasE—lemon balm extract, control
low; the concentration crop; MLF
of rosmarinic E—lemon
acid found balm
extract, phytosociological
in lemon (common) crop,
balm phytosociological cropresults weretimes
was 1.26 expressed
higherasthan
Mean ± SD
the (n = 3).
values recorded for
mint phytosociological crop.

(a)

Figure 2. Cont.
Plants 2022, 11,
Plants 2022, 11, 2398
2398 88 of
of 26
26

(b)
Figure 2.
Figure 2. (a)
(a) Menthae
Menthae extract,
extract, entire
entire spectra,
spectra, ESI
ESI−;
−; (A)—MM
(A)—MM EE and
and (B)—MF
(B)—MF E;
E; (b)
(b) Melissae
Melissae extract,
extract,
entire spectra, ESI−; (A)—MLM E and (B)—MLF E. Legend: PRO—Protocatechuic acid, RUT—Ru-
entire spectra, ESI−; (A)—MLM E and (B)—MLF E. Legend: PRO—Protocatechuic acid, RUT—Rutin,
tin, CAF—Caffeic acid, CHL—Chlorogenic acid, LUT—Luteolin, KAE—Kaempferol, ROS—Rosma-
CAF—Caffeic acid, CHL—Chlorogenic acid, LUT—Luteolin, KAE—Kaempferol, ROS—Rosmarinic
rinic acid, QUE—Quercetin, ISO—Isoquercitrin, FER—Ferulic acid, COU—p-Coumaric acid
acid, QUE—Quercetin, ISO—Isoquercitrin, FER—Ferulic acid, COU—p-Coumaric acid.
The quantitatively
2.7. Evaluation determined
of Antioxidant Activity polyphenolic compounds varied within broad limits
2.7.1. In Vitro Antioxidant Assaysused in the analysis. Although ferulic acid was identified
depending on the type of extract
by FT–ICR, the phytochemical could not be further quantified by this method, its concen-
The antioxidant effects observed for the tested extracts were directly correlated with
tration being possibly below the detection limit. Higher concentrations of protocatechuic
the concentration of secondary metabolites (Table 4). IC50 of Vitamin C was determined
acid were found in the lemon balm extracts compared to mint extracts, caffeic acid con-
by DPPH method and its value was 0.0165 mg/mL (Figure S47), IC50 of trolox was
centration was 15 times higher in the melissa extract obtained from the phytosociological
determined by ABTS method and its value was 0.0330 mg/mL (Figure S48) and IC50 of
crop in comparison with the control; the concentration of quercetin in the mint extract
FeSO4 was determined by FRAP method and its value was 0.1028 mg/mL (Figure S49).
obtained from the phytosociological batch was almost 20 times higher in comparison with
Data comparison revealed that the substances that generated the strongest antioxidant
the control crop; kaempferol was not quantified in the mint extract obtained from the con-
activities were found in MLF E (lowest IC50 value by all three methods, compared to the
trol crop, and in all other extracts the concentration was low; the concentration of rosma-
other extracts). It is especially noteworthy that the IC50 values for MLF E were, among the
rinic acid found in lemon balm phytosociological crop was 1.26 times higher than the val-
assessed extracts, substantially closer to the antioxidant values of the used control, which
ues recordedMLF
emphasizes for mint phytosociological
E’s superior antioxidantcrop.
action over the other samples. All the analyzed
extracts contained significant amounts of total polyphenols, with high concentrations for
2.7. Evaluation of Antioxidant Activity
MF E and MLF E, and moderate concentrations for MM E and MLM E. High amounts of
2.7.1. In Vitro
phenolic acidsAntioxidant
were also found Assaysin their composition, high concentrations being observed
for MFThe E antioxidant
and MLF E, effects
and moderate
observed concentrations
for the testedfor the other
extracts wereextracts
directly(Table 7). with
correlated
Furthermore, it is crucial to assess the relationships between the antioxidant
the concentration of secondary metabolites (Table 4). IC50 of Vitamin C was determined action of
the obtained extracts with TFL and total polyphenol content. The
by DPPH method and its value was 0.0165 mg/mL (Figure S47), IC50 of trolox was values of the Pearson
deter-
coefficient (r) are negative in all cases, which explains the inverse
mined by ABTS method and its value was 0.0330 mg/mL (Figure S48) and IC50 of FeSOcorrelation between the4
data (the higher the
was determined by amount of active
FRAP method andprinciples,
its valuethe
was lower themg/mL
0.1028 IC50 value of the
(Figure extracts
S49). Data
and therefore
comparison the stronger
revealed thesubstances
that the antioxidant action).
that A moderate
generated correlation
the strongest is observed
antioxidant activi-
between
ties werethe TFLin
found content
MLF Eand the IC50
(lowest IC50values
valuedetermined
by all three by the ABTS
methods, and DPPH
compared methods
to the other
(|r|
extracts). It is especially noteworthy that the IC50 values for MLF E were, among results
is between 0.40 and 0.69), but a very strong correlation was recorded for the the as-
obtained by the FRAP
sessed extracts, methodcloser
substantially (|r| >to0.900)—Table
the antioxidantS1. values of the used control, which
emphasizes MLF E’s superior antioxidant action over the other samples. All the analyzed
extracts contained significant amounts of total polyphenols, with high concentrations for
Plants 2022, 11, 2398 9 of 26

Table 7. Determination of antioxidant activity.

DPPH ABTS FRAP

Sample 95%CI 95%CI 95%CI
IC50 (mg/mL) IC50 (mg/mL) IC50 (mg/mL)
MM E 0.082 0.079–0.086 0.037 0.035–0.038 0.807 0.754–0.870
MF E 0.056 0.052–0.059 0.028 0.026–0.030 0.619 0.585–0.658
MLM E 0.048 0.040–0.055 0.027 0.024–0.029 0.756 0.689–0.836
MLF E 0.042 0.035–0.047 0.025 0.024–0.026 0.591 0.528–0.672
Vitamin C 0.016 0.0160–0.0169 –* –*
Trolox –* 0.033 0.028–0.037 –*
FeSO4 –* –* 0.102 0.098–0.106
DPPH: 2,2-diphenyl-1-picryl-hydrazine; ABTS: 2,20-azinobis-3-ethylbenzotiazoline-6-sulfonic acid; FRAP: ferric
reducing antioxidant power, 95%CI—95% confidence interval of IC50, “–*” = the standard has not been used for
this method.

The content of total polyphenols (TPC) in direct correlation with the antioxidant
activity of plant extracts, the compared data (TPC concentration vs. IC50) showing a
moderate correlation in the case of the DPPH and ABTS methods and a strong correlation
for the FRAP method—Table S1.
It was observed that the IC50 values determined by the FRAP method proved to be
much better correlated with the content of active principles (TFL and TPC) than those
provided by other assaying methods. The evaluation of the antioxidant action by the
three methods (DPPH, ABTS, FRAP) is consistent with the results obtained for the deter-
mination of polyphenol content. The high concentrations of polyphenols in the extracts
obtained from the plant products of the phytosociological crops could also explain their
significantly higher antioxidant action.

2.7.2. In Silico Studies

A set of 11 polyphenolic ligands were docked into the binding sites of three sirtuin
isoforms to evaluate the potential of such compounds to act as direct activators. The
implemented docking protocol was successfully validated, and the predicted binding
poses superposed on the experimental conformations are shown in Figure S50. Only slight
variations in ligand orientation were observed for all four positive controls. The SIRT1 and
SIRT5 activator resveratrol showed a binding energy of −9.332 kcal/mol and 0.549 ligand
efficiency for SIRT1, and a much higher binding energy of −5.220 for SIRT5 (0.307 ligand
efficiency). The SIRT6 activator quercetin had a binding energy of −6.899 kcal/mol and
0.314 ligand efficiency, while the SIRT6 inhibitor catechin gallate, a quercetin derivative,
had a docking score of −8.732 kcal/mol and 0.273 ligand efficiency. Although catechin
gallate is structurally similar to quercetin and shares the same binding pocket, previous
studies showed that the differences in ligand and protein sidechain orientations within
the binding site are responsible for a total shift in biological activity [21]. Thus, the studies
polyphenols were docked into both protein conformations, in order to discriminate between
potential stimulatory and inhibitory activities.
The binding energies and ligand efficiencies obtained after the docking simulations are
shown in Table 8, while the predicted dissociation constants are presented in Table S2. The
binding energies after docking on SIRT1 ranged from −9.827 kcal/mol to −5.858 kcal/mol,
with a mean value of −8.430 ± 1.337 kcal/mol. For SIRT5, docking scores varied between
−8.764 and −5.720 kcal/mol, with a mean of −7.217 ± 1.104 kcal/mol. Binding ener-
gies after docking on the activator-specific conformation of SIRT5 ranged from −7.775 to
−5.721 kcal/mol (−6.698 ± 0.602 kcal/mol), while energies for the inhibitor-specific recep-
tor conformation were between −8.287 and −5.703 kcal/mol (−6.774 ± 0.860 kcal/mol).
Plants 2022, 11, 2398 10 of 26

Table 8. Molecular docking results for selected sirtuin isoforms.

SIRT1 (Activator) SIRT5 (Activator) SIRT6 (Activator) SIRT6 (Inhibitor)

Ligand ∆G (kcal/mol) LE ∆G (kcal/mol) LE ∆G (kcal/mol) LE ∆G (kcal/mol) LE
Caffeic acid −7.186 0.553 −6.224 0.479 −6.274 0.483 −6.411 0.493
Chlorogenic acid −8.027 0.321 −7.212 0.289 −6.609 0.264 −7.262 0.291
Ferulic acid −7.334 0.524 −6.057 0.433 −5.721 0.409 −6.172 0.441
Isoquercitrin −8.995 0.273 −8.205 0.249 −6.460 0.196 −5.865 0.178
Kaempferol −9.827 0.468 −7.583 0.361 −6.690 0.319 −6.787 0.323
Luteolin −9.520 0.453 −7.962 0.379 −6.419 0.306 −7.279 0.347
p-Coumaric acid −7.376 0.615 −5.720 0.477 −6.977 0.581 −5.900 0.492
Protocatechuic acid −5.858 0.533 −5.750 0.523 −6.232 0.567 −5.703 0.519
Quercetin −9.259 0.421 −7.554 0.343 −6.899 * 0.314 * −6.912 0.314
Rosmarinic acid −9.638 0.371 −8.357 0.321 −7.775 0.299 −8.287 0.319
Rutin −9.709 0.226 −8.764 0.204 −7.623 0.177 −7.940 0.185
Resveratrol * −9.332 0.549 −5.220 0.307 - - - -
Catechin gallate * - - - - - - −8.732 0.273
∆G—binding energy; LE—ligand efficiency; *—positive control.

When compared to the positive controls, we found that four compounds exhibited
higher binding affinities for SIRT1 (rutin, rosmarinic acid, luteolin and kaempferol), all
polyphenols had higher affinities for SIRT5 (although only eight had better ligand effi-
ciencies), three ligands showed better energies for SIRT6 as potential activators (rutin,
rosmarinic acid, p-coumaric acid) and no compounds had better affinities as potential
inhibitors, but nine compounds showed better ligand efficiencies. Interestingly, quercetin
showed a slightly better binding energy for the SIRT6 inhibitor binding site, although the
ligand efficiencies were practically equal. Moreover, luteolin had a better binding affinity
for the same binding site, although previous data indicate that luteolin is a SIRT6 activator,
rather than an inhibitor [21]. Thus, the docked conformation should be a better indicator of
a potential stimulatory or inhibitory activity, rather than the binding energy. On the other
hand, isoquercitrin had a much better binding affinity for the SIRT6 activator pocket and
was proven to stimulate SIRT6 activity [21].
Regarding the molecular interactions between docked ligands and target proteins, we
chose to discuss the predicted interactions for one particular compound, rosmarinic acid,
which showed both good docking scores and ligand conformations. Moreover, rosmarinic
acid had predicted dissociation constant values of nanomolar range for SIRT1 (86 nM0,
while the potencies for other isoforms were of 0.749 µM for SIRT5, 1.999 µM for SIRT6
as activator and 0.842 µM for SIRT6 as inhibitor. Rosmarinic acid formed four hydrogen
bonds with SIRT1 binding site, involving residues Asn226, Glu230 and Phe414. Moreover,
the ligand formed one additional hydrogen bond with Lys3, which is part of the peptide
substrate, thus stabilizing the sirtuin-substrate complex. Furthermore, rosmarinic acid
formed hydrophobic pi–alkyl interactions with Pro212, Leu215, Arg446 and Pro447 and
van der Waals interactions with other residues (Figure 3a,b).
The complex between rosmarinic acid and SIRT5 is stabilized by hydrogen bonds with
Gln140, Asp143 and His158. Two arginine residues are involved in one salt bridge with
the carboxylic moiety and one pi–cation interaction with the phenyl ring. Hydrophobic
interactions such as pi–alkyl interactions and weak van der Waals forces are observed with
other residues within the binding pocket. Unfortunately, one unfavorable acceptor–acceptor
interaction was formed between one hydroxyl group and Asp143 (Figure 3c,d).
Rosmarinic acid showed a better binding energy for the binding pocket specific to
the SIRT6 inhibitor catechin gallate. However, rosmarinic acid interacted fairly well with
the pocket specific to the SIRT6 activator quercetin. Regarding the quercetin binding
pocket, rosmarinic acid formed several polar interactions such as three hydrogen bonds
with Thr84 and Tyr257, and one hydrogen bond with a water molecule. A pi–pi stacked
interaction was formed with Phe82 and several other van der Waals interactions with
other residues and a water molecule (Figure 4a,b). The docking experiment revealed that
rosmarinic acid occupied a binding subpocket proximal to the inhibitor binding site. The
interaction between rosmarinic acid and the inhibitor-specific crystal structure of SIRT6 was
Plants 2022, 11, 2398 11 of 26

characterized by two hydrogen bonds with Arg65 and ADP-ribose (AR6401). Noteworthy
is the fact that the interaction with ADP–ribose was not reported for the inhibitor catechin
gallate, which indicated that the predicted conformation of rosmarinic acid might not
correspond to a potential SIRT6 inhibitory activity. Moreover, the ligand forms an attractive
charge interaction with Lys160, a pi–pi stacked interaction with Trp188 and several van
der Waals interactions. On the other hand, the phytochemical three types of unfavorable
Plants 2022, 11, 2398 interactions: unfavorable negative charge interactions (Asp187), and unfavorable11donor–
of 26
donor (ADP–ribose) and acceptor–acceptor interactions (Pro10, Figure 4c,d).

Figure 3.
Figure 3. Predicted
Predicted ligand
ligand poses
poses and
and molecular
molecularinteractions
interactionsbetween
betweenrosmarinic
rosmarinicacid
acidand
andSIRT1
SIRT1and
and
SIRT5. (a)—3D conformation of predicted rosmarinic acid-SIRT1 complex; (b)—2D representation
SIRT5. (a)—3D conformation of predicted rosmarinic acid-SIRT1 complex; (b)—2D representation of
of protein–ligand interactions for predicted rosmarinic acid–SIRT1; (c)—3D conformation of pre-
protein–ligand interactions for predicted rosmarinic acid–SIRT1; (c)—3D conformation of predicted
dicted rosmarinic acid–SIRT5 complex; (d)—2D representation of protein–ligand interactions for
rosmarinic acid–SIRT5acid–SIRT5
predicted rosmarinic complex; (d)—2D representation of protein–ligand interactions for predicted
complex.
rosmarinic acid–SIRT5 complex.
The complex between rosmarinic acid and SIRT5 is stabilized by hydrogen bonds
with Gln140, Asp143 and His158. Two arginine residues are involved in one salt bridge
with the carboxylic moiety and one pi–cation interaction with the phenyl ring. Hydropho-
bic interactions such as pi–alkyl interactions and weak van der Waals forces are observed
with other residues within the binding pocket. Unfortunately, one unfavorable acceptor–
acceptor interaction was formed between one hydroxyl group and Asp143 (Figure 3c,d).
Rosmarinic acid showed a better binding energy for the binding pocket specific to
the SIRT6 inhibitor catechin gallate. However, rosmarinic acid interacted fairly well with
 was characterized by two hydrogen bonds with Arg65 and ADP-ribose (AR6401). Note-
worthy is the fact that the interaction with ADP–ribose was not reported for the inhibitor
catechin gallate, which indicated that the predicted conformation of rosmarinic acid might
not correspond to a potential SIRT6 inhibitory activity. Moreover, the ligand forms an
attractive charge interaction with Lys160, a pi–pi stacked interaction with Trp188 and sev-
Plants 2022, 11, 2398 eral van der Waals interactions. On the other hand, the phytochemical three types of 12 un-
of 26
favorable interactions: unfavorable negative charge interactions (Asp187), and unfavora-
ble donor–donor (ADP–ribose) and acceptor–acceptor interactions (Pro10, Figure 4c,d).

Figure
Figure 4. 4.Predicted
Predictedligand
ligand poses
poses and
and molecular
molecular interactions
interactionsbetween
betweenrosmarinic acid
rosmarinic andand
acid SIRT6.
SIRT6.
(a)—3D conformation of predicted rosmarinic acid–SIRT6 complex (activator binding pocket); (b)—
(a)—3D conformation of predicted rosmarinic acid–SIRT6 complex (activator binding pocket);
2D representation of protein–ligand interactions for predicted rosmarinic acid–SIRT6 (activator
(b)—2D
bindingrepresentation
pocket); (c)—3D ofconformation
protein–ligand interactions
of predicted for predicted
rosmarinic rosmarinic
acid–SIRT6 acid–SIRT6
complex (inhibitor (acti-
bind-
vator
ing binding
pocket); pocket);
(d)—2D (c)—3D conformation
representation of predicted
of protein–ligand rosmarinic
interactions foracid–SIRT6 complex (inhibitor
predicted rosmarinic acid–
SIRT6 complex
binding pocket); (inhibitor
(d)—2D binding pocket). of protein–ligand interactions for predicted rosmarinic
representation
acid–SIRT6 complex (inhibitor binding pocket).

The free energies of binding obtained after performing MM/PBSA (molecular me-
chanics Poisson–Boltzmann surface area) calculations on the last snapshot of the 1 ns
molecular dynamics simulations are shown in Table S3. The performed analysis revealed
that rosmarinic acid exhibited much lower free binding energies than two out of three
positive controls. Thus, the predicted ligand showed higher binding affinities after 1 ns
of simulation than resveratrol for both SIRT1 and SIRT5 isoforms, and higher than SIRT6
activator quercetin. On the other hand, rosmarinic acid had a higher binding energy than
the SIRT6 inhibitor catechin gallate. The lowest energy was recorded for the interaction
with SIRT6, followed by SIRT5 and SIRT1, respectively. Therefore, the free energy of bind-
ing calculations further strengthened the hypothesis that rosmarinic acid may have the
potential to activate SIRT6, rather than inhibiting the isoform, while also possibly acting as
SIRT1 and SIRT5 direct activators.
Plants 2022, 11, 2398 13 of 26

3. Discussion
In this current study, Menthae folium and Melissae folium plant products harvested
from species grown in common (phytosociological) crops were analyzed in comparison
with control crops. The crops were grown on an agricultural field, in Teleorman county,
near Turnu Măgurele, Romania. The obtained results are in agreement with previously
published data from our research [22,23], when the raw material for 2019 and 2020 was
analyzed. Growing the two species in common batches is beneficial not only for their
horizontal and vertical development or generation of a large mass of plant material, but
also for the biosynthesis of a significantly higher amount of polyphenols.
The quantitative chemical profile of the plant raw materials was determined by spec-
trophotometric methods and polyphenolic derivatives were assessed (flavones and to-
tal polyphenols). Although spectrophotometric methods cannot be considered selective
methods of analysis (possible interference with other types of constituents), they pro-
vide information regarding the polyphenol content, and they are frequently used and
described in European Pharmacopoeia 10th edition (Chapter 8.8.14. Tannis in herbal drugs;
dosage of flavones in various plant product monographs, e.g., Betulae folium—expressed in
hyperoside; Sambuci flos—expressed in isoquercitroside).
From a statistical point of view, it was found that there was an interdependence
between the content of active principles and the batch from which the plant raw material
came from (single crop vs. phytosociological crop). Statistical differences were observed in
the content of total polyphenols only for lemon balm.
In order to determine the influence of fertilizers on polyphenol biosynthesis, as-
sessments were also performed on plant products harvested from species grown on the
farmland where one chemical (NPK) and one organic fertilizer were used.
We consider weak alkaline soil to be beneficial to the culture, given the quantitative
chemical results presented above. Soil humus is a complex mixture of compounds resulting
from the transformation of organic and microbial residues. With a concentration of almost
3% in humus, we can consider it an average soil enriched in these natural complexes. The
three macronutrients in the soil, nitrogen, phosphorus and potassium are very important
for plant development. The presence of nitrogen and phosphorus in the soil is important
for stimulating the root growth of medicinal plants, and for nutrient uptake. Potassium
increases plant mass production and improves their quality [24]. Soil trace element content
is correlated with soil quality. The crops were grown in an ecological area of Teleorman
county, for this reason we consider that the soil has low concentrations of the analyzed
trace elements.
The comparison between soil fertilization with organic and NPK fertilizers was per-
formed to assess their influences on the amount of active ingredients produced by the
respective plant raw materials. Although the crop species from the soil fertilized with NPK
were better developed and generated a greater amount of plant raw material, the polyphe-
nols were biosynthesized in much lower concentrations. For example, M Bio generated
1.3-fold more TFL compared to M NPK and 1.5-fold more TPC. In the lemon balm crops,
the highest variation in active compounds was observed for TFL. In the BIO fertilized
crop, the concentration was 1.7-fold higher compared to the ML NPK crop, while the TPC
was 1.18-fold higher. When compared to the unfertilized batches, the most important
differences were observed for the crops where the BIO fertilizer was used.
The use of fertilizers for mint samples was also reported by other researchers: Hend S et al. [25]
investigated the influence of fertilizer types on volatile oil production. Sheykholeslami Z. et al. [26]
found that soil treatment with different types of fertilizers was beneficial to the development
of Mentha piperita L. species, a higher quantity of plant product was generated, and vertical
growth was also significantly higher [27]. According to studies by Marin N. et al. [28], on a
field located in Teleorman county, a successive fertilization of the soil did not lead to an
overload with trace elements, a finding also observed during our research on soil enriched
with the two types of fertilizers. For instance, the concentration of manganese quantified in
NPK-fertilized soil is much lower compared to the data found in the literature [24].
Plants 2022, 11, 2398 14 of 26

Dry extracts were also obtained from samples retrieved from species grown in fertilizer-free
plots. For these extracts, we determined the polyphenolic profile by spectrophotometric,
FT–ICR MS and UHPLC–MS methods, and we also investigated the antioxidant activity.
Growing in phytosociological crops can be a practice that can be extended to medicinal
plants. Enhancement of horizontal and vertical development, and generation of a larger
quantity of plant mass enriched in active ingredients can be the basis for further studies,
and the relevant findings could be transferred to indigenous producers of medicinal plant
crops. Plant products from common (phytosociological) batches have a higher amount
of polyphenols, which varies greatly depending on the nature of the plant raw material.
Extractions of polyphenols from plant products were made in 50% (for mint) and 70% (for
lemon balm) ethanol, since previous studies reported that these concentrations were shown
to yield the best results [22,23]. At the same time, we aimed to use solvents that are more
environmentally friendly and do not generate toxic metabolites.
Mint and lemon balm are species belonging to the same family (Lamiaceae), are aromatic
plants, and can be positively influenced (as shown for polyphenol content) by being
cultivated in common crops. Hydroethanolic plant extracts were prepared from common
and control batches.
Extracts obtained from plant products harvested from the common crops had a sig-
nificantly higher polyphenol content compared to the control crops. There was a high
accumulation in total polyphenols compared to flavones; e.g., in the mint extract obtained
from the common batch products, the concentration in total polyphenols was 4.7-fold
higher compared to flavones, and in lemon balm there were 7.3-fold more total polyphenols
compared to flavones.
FT–ICR MS and UHPLC–MS analysis allowed the identification and quantification of
polyphenol content; increased concentrations of polyphenols were found in lemon balm
for caffeic acid, chlorogenic acid and luteolin. The Melissa extract obtained from the plant
product harvested from the common (phytosociological) crop contained 3.7 times more
caffeic acid compared to mint harvested from the same crop, 4.5 times more chlorogenic
acid and 6.3 times more luteolin. In the control batches, the differences between the two
species in the active principles content was much smaller. Based on the obtained results,
we can conclude that the association of the two species in phytosociological culture leads
to an enrichment in polyphenol-type phytoconstituents.
Although it was found in small quantities in the analyzed batches, protocatechuic acid
(3,4-dihydroxybenzoic acid) is of high importance, since this phytochemical is considered
to be a perfect peroxyl radical scavenger in the polar medium of aqueous solutions, and a
relatively good free radical scavenger in the non-polar medium of lipid solutions. It is able
to attenuate oxidative stress by increasing glutathione peroxidase (GSH-Px) and superox-
ide dismutase (SOD) activity, as well as reducing xanthine oxidase (XOD) and NADPH
oxidase (NOX) activity and malondialdehyde (MDA) concentrations [29]. Phytotherapy
supplementation with extracts rich in rutin (quercetol 3-rhamnoglucoside) is beneficial,
given the multiple therapeutic virtues it presents [30], such as preventing the oxidation of
LDL-cholesterol involved in atherosclerosis [31]. Furthermore, rutin has been shown to be
effective in terms of free radical scavenging capacity (presence of the four phenolic hydroxyl
groups in the chemical structure), may be a potential hydrogen donor, and has been shown
to have a higher DPPH radical scavenging capacity than vitamin C [32–34]. Luteolin, a
flavone derivative found in a wide variety of vegetables and fruits, with an average daily
intake of 0.01–0.20 mg/day [35], is implicated in a variety of therapeutic effects at the
cellular level (cardioprotective, hypocholesterolemic, antitumor, anti-inflammatory) due to
its antioxidant effects [36–39]. Caffeic acid (3,4-dihydroxycinnamic acid) has been shown
to be a protector of alpha-tocopherol in low-density lipoprotein (LDL) [40], and is a com-
pound with a clearly superior antioxidant activity against LDL-cholesterol oxidation, when
compared to p-coumaric and ferulic acid [41,42]. Rosmarinic acid, a phenolic compound
derived from hydroxycinnamic acid, is frequently found in species of the Lamiaceae family,
Plants 2022, 11, 2398 15 of 26

and is recognized for its antioxidant, anti-inflammatory, hepatoprotective, cardioprotective

and neuroprotective activities [43].
The intensity of the antioxidant action is dependent on the polyphenol content for each
type of the analyzed extracts. DPPH radical inhibition is 0.7-fold higher for common batch
lemon balm extract compared to mint extract. Furthermore, a 0.8-fold higher reduction
of the non-biological radical ABTS and 0.9-fold higher antioxidant power for ferric ion
reduction were observed. Considering that, from a mathematical point of view, the Pearson
correlation coefficient has certain intervals that express the degree of correlation between
the experimental data sets, where we obtained values lower than 0.900 for the r coefficient,
we can quantify the existing relationship between the analyzed data even if statistically we
cannot extrapolate what we observed to the entire target population.
The antioxidant potential of the studied extracts was also evaluated using in silico
methods. Molecular docking simulations were carried out to investigate the potential
interactions between identified polyphenols and three sirtuin isoforms (SIRT1, SIRT5
and SIRT6), as a means to predict the stimulatory activity on endogenous antioxidant
defense mechanisms. Moreover, the available crystal structure of SRT6 in complex with
a natural inhibitor (catechin gallate) allowed us to discriminate between activators and
inhibitors. Interestingly, none of the docked compounds showed conformations in the
catechin gallate allosteric binding site that resembled the orientation of the positive control,
even though caffeic acid, chlorogenic acid, ferulic acid, kaempferol, luteolin, quercetin,
rosmarinic acid and rutin had better binding affinities for this receptor structure. Except for
protocatechuic acid, all docked ligands showed rather high binding affinities for SIRT1 and
could act as direct SIRT1 activators by stabilizing the complex between the enzyme and
substrate. Furthermore, quercetin, ferulic acid, caffeic acid ethanolamide, chlorogenic acid,
kaempferol, luteolin and protocatechuic acid were shown to up-regulate SIRT1 activity in
various experimental settings [44–48]. Moreover, other authors hinted that rosmarinic acid,
which we discussed in more detail, demonstrated anti-inflammatory and anti-apoptotic
effects in a mouse model of nonalcoholic steatohepatitis, possibly due to stimulating
SIRT1-mediated pathways [49]. On the other hand, quercetin can directly inhibit SIRT1
activity [21]. Rosmarinic acid, rutin and isoquercitrin showed particularly high binding
affinities for SIRT5. No data were found in the literature regarding the first two compounds,
while isoquercitrin was shown to be active only on SIRT6. The same study highlighted that
SIRT6 is activated also by luteolin and quercetin [21].
Predicted dissociation constants were also calculated after molecular docking simula-
tions. The docking experiments revealed that isoquercetin, kaempferol, luteolin, quercetin,
rosmarinic acid and rutin had Kd values lower than 1 µM for SIRT1, while only isoquercetin,
rosmarinic acid and rutin had Kd values within the same range for SIRT5. However, as
potential SIRT6 activators, only p-coumaric acid, rosmarinic acid and rutin had Kd values
ranging between 1 and 10 µM, the lowest being 1.999 µM for rosmarinic acid. Among
these compounds, rutin, luteolin, rosmarinic acid, quercetin and isoquercetin were found
in relatively high concentrations in both phytosociological plant extracts. Another phyto-
chemical detected in high amounts was caffeic acid, for which docking simulations showed
relatively lower potency values, but remarkably high ligand efficiencies. Furthermore,
the aforementioned polyphenols could act as potent antioxidants through both direct and
indirect mechanisms, in a synergistic manner: by acting as free radical scavengers and
promoters of antioxidant defenses through direct stimulation of sirtuins.
A more detailed analysis of the molecular interactions between rosmarinic acid and
sirtuins supported the potential to directly activate SIRT1, 5 and 6, rather than inhibit
SIRT6. These observations were also strengthened by the MM/PBSA binding free energy
calculations, which revealed that rosmarinic acid had markedly lower binding energies
than SIRT1 and SIRT5 activator resveratrol and SIRT6 activator quercetin, while exhibiting a
higher energy than SIRT6 inhibitor catechin gallate. Among the three isoforms, rosmarinic
acid showed the lowest binding free energy for SIRT6. Therefore, the radical scavenging
activity of the studied extracts might be complemented in vivo by the up-regulation of
Plants 2022, 11, 2398 16 of 26

sirtuins activity by rosmarinic acid and other phytochemical constituents, thus leading to
an enhanced antioxidant protection in various diseases.

4. Materials and Methods

4.1. Establishing the Quality of Plant Raw Materials
We determined the quality of the raw materials using classic and common spectropho-
tometric methods, cited in the literature and frequently applied in the assessment of these
types of active principles. Since plant extracts are mixtures of many complex substances,
these determinations are frequently used. Even the UHPLC MS method confirmed the
identity of the globally assessed compounds in the plant raw materials.

4.1.1. Plant Materials, Reagents and Equipment

Back in 2018, we started to cultivate in common (phytosociological) crops two medic-
inal plants, Mentha piperita L and Melissa officinalis L. Peppermint and lemon balm were
planted using experimental plots with following characteristics: area of 50 cm × 300 cm,
400 cm between batches, 30 cm between seedlings and 5 seedlings per group. The cultures
were grown in Turnu Magurele City’s suburbs in Teleorman County (43◦ 440 44.1600 Northern
latitude, 24◦ 520 53.4000 Eastern longitude), Romania [22]. This area presents average yearly
temperatures of 11.5 ◦ C, average monthly temperatures of 23 ◦ C for the warm ones and
average monthly temperatures less than 2 ◦ C for the cold ones. It is distinguished by a high
caloric potential, high air temperature amplitudes, little precipitation, frequent torrential
regime in the summer and frequent drought intervals. In order to avoid being influenced,
the control crops were planted apart from the common culture. By comparing each crop
with the control batch, the morphological and phytochemical characteristics of the harvest
were investigated [23]. In July of each year, the plants were collected and dried in laboratory
conditions at the department of Pharmacognosy, Phytochemistry and Phytotherapy of the
Faculty of Pharmacy. The study took place during 2018–2021 and the data collected in 2021
are presented in this paper.
Based on previous studies [22], the solvents used for the extraction of active principles
were 50% ethanol for mint (MM—peppermint leaves from control crop, MF—peppermint
leaves from common crop) and 70% ethanol for lemon balm (MLM—lemon balm leaves
from control crop, MLF—lemon balm leaves from control crop). The solvent was chosen
to ensure the best possible extraction of phenolic constituents from all the examined
leaves. The ethanol used as solvent in this section was purchased from Sigma–Aldrich,
Hamburg, Germany.
Approximately 1.000 g of dried leaves from each plant was brought into 50 mL ethanol
and then subjected to refluxing for 30 min. On the extractive solution obtained by filtration
in a 50 mL flask [22], we performed further analyses presented in the following paragraphs.

4.1.2. Determination of Polyphenolic Content

Total flavonoid content (TFL) and total phenolic content (TPC) were all determined
using spectrophotometric techniques.

Determination of Total Flavonoids Content (TFL)

The total flavonoids content assay utilized a colorimetric technique based on the re-
action between flavonoids and AlCl3 . From our obtained extractive solutions, we made
dilutions of 10:25 mL and, thereafter, 5 different volumes were brought into 10 mL volu-
metric flasks. Then, 2 mL sodium acetate 100 g/L (Sigma–Aldrich, Hamburg, Germany)
and 1 mL aluminium chloride solution 25 g/L (Sigma–Aldrich, Hamburg, Germany) were
added. Further, all the volumes were adjusted to 10 mL by adding the same solvent as
above. In parallel with the samples to be analyzed, the appropriate control samples were
prepared in the same conditions but without sodium acetate and aluminum chloride. After
45 min, the absorbance was measured at 427 nm (Jasco V–530 spectrophotometer, Hachioji,
Japan). Rutin (Sigma–Aldrich, Hamburg, Germany) was used as a standard for the linear
Plants 2022, 11, 2398 17 of 26

calibration curve in the concentration range of 5–35 µg/mL with R2 = 0.9992. The total
flavonoids content (TF) of the extract was expressed as mg rutin equivalents per gram of
sample (mg/g) [50].

Determination of Total Phenolic Content (TPC)

Total polyphenols (TPC) were determined in accordance with Lamuela–Raventós’s [51]
methodology with a few minor adjustments. Same dilution was used and volumes between
0.1 mL and 0.6 mL were brought into 10 mL volumetric flasks and were adjusted to 1 mL
by adding distilled water. Then, the volumes were mixed with 1 mL Folin–Ciocalteu’s
phenol reagent (Sigma–Aldrich, Hamburg, Germany) and kept at 25 ◦ C for 5–8 min before
adding 8 mL sodium carbonate solution 200 g/L (Sigma–Aldrich, Hamburg, Germany).
After 40 min in dark conditions, the absorbance was measured at 725 nm (Jasco V–530
spectrophotometer, Hachioji, Japan). The absorbance was measured relative to a blank
sample obtained by mixing 1 mL distilled water with 1 mL Folin–Ciocalteu’s reagent and
then adjusted to 10 mL by adding sodium carbonate. Tannic acid (Sigma–Aldrich, Hamburg,
Germany) was used as a standard for the calibration curve in a linear concentration range
of 2–9 µg/mL with R2 = 0.999. The total phenolic content (TP) was expressed as mg tannic
acid equivalents per gram of sample (mg/g) [50].

4.2. The Influence of Fertilizers on the Biosynthesis of Secondary Metabolites

4.2.1. Assessment of Soil Composition and Plant Material
Soil samples have been taken from several areas at a depth of 10–15 cm and the
concentrations of micro and macroelements was assessed. These determinations were
performed at Physico-Chemical Analysis Laboratory for Soil Sciences, Agrochemistry and
Environmental Protection (LAFC) within the National Research-Development Institute for
Pedology, Agrochemistry and Environmental Protection (ICPA), represented by Head of
Laboratory, Dr. Nicoleta Vrînceanu, as executor of the tests.
The parameters evaluated to determine the quality of control and fertilized soil,
also NPK 20–20–20 and Bio–Fertil 20 formulas can be found in Supplementary Materials
Sections S2.1–S2.3. Through these methods described there, we determined the presence
and concentrations of N, P, K, Ca, Zn, Cu, Fe and Mn.
Moreover, the widely described methods by which the macro- and microelements in the
plants’ leaves obtained on these soils were analyzed are presented in the Supplementary Materials.

4.2.2. Determination of the Quality of Extractive Solutions from Fertilized Material

Spectrophotometric methods that were used for the determination of total flavonoid
content (TFL) and total phenolic content (TPC) are presented in Section 4.1.2.

4.3. Plant Extracts Preparation

Dry leaves from M–ML common and control crops were used for obtaining dry
extracts. Based on our previous study [22], the solvent used for the extraction was 50%
ethanol for all plants. Exactly 25 g of plant material were used from every crop and were
subjected to two consecutive reflux extraction processes: the first extraction used 1.5 L
solvent for 30 min, while the second used 750 mL solvent for 30 min. The two extract
solutions were mixed and concentrated in a rotary evaporator (Buchi, Vacuum Pump V-700)
and then subjected to a lyophilization process (Christ Alpha 1–2/B Braun, BiotechInt, New
Delhi, India). The dry extracts were conserved in a glass vacuum desiccator [50]. The
samples were marked as follows: MM E (Mentha extract from control crop), MF E (Mentha
extract from common crop), MLM E (Melissa extract from control crop) and MLF E (Melissa
extract from common crop). Each stage of the research includes a presentation of additional
tools and experimental setups used in this investigation.
Plants 2022, 11, 2398 18 of 26

4.4. Phytochemical Analysis of Plant Extracts

Spectrophotometric methods used for the quality control of plant extracts are described
at 4.1.2. (Determination of Polyphenolic Content). In the case of FT–ICR MS, the technique
allows the identification of a minimum of 300 compounds using direct electrospray infusion
ionization, without chromatographic separation, depending on the monoisotopic mass
in a very short time. The hyphenated method known as Ultra-High Performance Liquid
Chromatography (UHPLC–MS) was used to establish the polyphenolic profile of the plant
extracts based on non-targeted tandem mass spectrometry (MS–MS). The same method
was used for the quantification of selected polyphenolic compounds for each available
analytical standard (Sigma–Aldrich, Hamburg, Germany).

4.4.1. Assessment of TFL and TPC

Analytical determination of TFL and TPC was performed according to the method
described at 4.1.2. (Determination of Polyphenolic Content).

4.4.2. Identification of Polyphenolic Compounds by FT–ICR MS

FT–ICR MS with 15T superconducting magnet (solar X–XR, QqqFT–ICR HR, Bruker
Daltonics) was used for electrospray ionization (ESI) analysis (HR–MS). For negative ESI
ionization, the sample was introduced by direct infusion, with a sample flow rate of
120 µL/h, a nebulizing gas pressure (N2 ) of 4 bar at 200 ◦ C, and a flow rate of 7 L/min. The
spectra were recorded over a mass range between 46 and 800 uam at a source voltage of
5700 V. For the positive ESI ionization, the sample was introduced by direct infusion, with
a sample flow rate of 120 µL/h, a nebulizing gas pressure (N2) of 3.2 bar at 180 ◦ C, and a
flow rate of 5 L/min. The spectra were recorded in a mass range between 46 and 800 uam
at a source voltage of 5500 V.
It is well acknowledged that Fourier transform ion cyclotron resonance mass spec-
trometry (FT–ICR MS) is one of the most effective methods for analyzing organic mixtures
at the molecular level. It is frequently possible to identify organic molecules using only
the recorded mass-to-charge (m/z) values due to the ultra-high mass resolution of FT–ICR
MS. Organic mixtures such as metabolites [52], vegetal oils [53], wine [54], explosives [55],
coal extracts, [56], humic materials [57,58] as well as crude oils [59,60], have all been effec-
tively analyzed using FT–ICR MS. Broadband FT–ICR MS spectra of these types of organic
combinations are usually very complicated, with peaks appearing across a large dynamic
range [56].

4.4.3. Identification and Quantification of Polyphenolic Compounds by Ultra-High

Performance Liquid Chromatography–MS (UHPLC–MS)
Reagents: Protocatechuic (PRO), caffeic (CAF), p-coumaric (COU) and ferulic (FER)
acids were purchased from Merck (Kenilworth, NJ, USA), chlorogenic (CHL) acid was
obtained from Alfa Aesar (Haverhill, MA, USA), rosmarinic (ROS) acid, rutin (RUT) and
quercetin (QUE) were acquired from Sigma Aldrich, luteolin (LUT) and kaempferol (KAE)
were purchased from Roth (Dautphetal, Germany), while isoquercitrin (ISO) was obtained
from HWI Analytik (Rülzheim, Germany). All HPLC gradient grade solvents (water,
acetonitrile) were purchased from Merck. The calibration curve for this method with
standard chromatogram, and retention times can be found in Supplementary Materials,
Section S2.4 (Tables S4 and S5, Figure S51).

4.5. Evaluation of Antioxidant Activity

4.5.1. In Vitro Assays
DPPH Free Radical Scavenging Activity (2,2-Diphenyl-1-picrylhydrazyl)
According to Celik S.E., the antioxidant activity is influenced by both the properties of
the substrate and the polarity of the solvent. The DPPH assay was used to measure the free
radical scavenging activity of the plant extracts [61]. Equal amounts of 0.1 g dry extracts
were dissolved in 100 mL 50% ethanol for all dry extracts. Ten corresponding volumes of
Plants 2022, 11, 2398 19 of 26

each obtained solution were brought into 10 mL volumetric flasks and were adjusted to
10 mL by adding the same solvent as above. 0.5 mL of each diluted solution was mixed
with 3 mL DPPH 0.1 mM radical solution (Sigma–Aldrich, Hamburg, Germany) [62]. The
solutions were protected against light for 30 min, and the absorbance was then measured at
515 nm using a spectrophotometer (Jasco, Hachioji, Japan). Ascorbic acid (Sigma–Aldrich,
Hamburg, Germany) was used as a reference for the calibration curve in the concentration
range of 2–22 µg/mL [50].
The percentage of DPPH• inhibition was calculated using the formula below [63]:

A (blank) − A (sample)
% DPPH inhibition = × 100 (1)
A (blank )

where:
A (blank) = blank absorbance of DPPH 0.1 mM solution in the absence of extracts
(1.00 ± 0.10);
A (sample) = sample absorbance of the DPPH solution in the presence of extracts after
30 min.
Based on the established values, inhibition curves (%) were constructed depending
on the concentration (mg/mL). Using the linear equations, the IC50 values (mg/mL) were
determined for each extract (for the value y = 0.5).

ABTS Method of Total Antioxidant Capacity Assessment

Due to the fact that the antioxidant response involves faster reaction kinetics in a
pH-independent way, the ABTS assay is regarded as one of the most sensitive assays to
evaluate the antioxidant activity of both hydrophilic and lipophilic substances [64,65].
The reaction of ABTS (Sigma–Aldrich, Hamburg, Germany) 7.4 mM solution with
potassium persulfate 2.6 mM (K2 S2 O8 —Sigma–Aldrich, Hamburg, Germany) produced the
ABTS radical cation (ABTS•+ ), which was then stored at room temperature and in darkness
for 16 h before use [66].
Equal amounts of 0.1g dry extracts were dissolved in 100 mL 50% ethanol for every
plant extract used in our study. Seven corresponding volumes of each obtained solution
were brought into volumetric flasks and adjusted to 10 mL by adding the same solvent
as above. 0.5 mL of each diluted solution was mixed with 3 mL ABTS•+ solution diluted
with ethanol (Sigma–Aldrich, Hamburg, Germany). The solutions were stirred and held in
darkness for 6 min [67]. The absorbance was then measured at 734 nm, relative to absolute
ethanol, using a spectrophotometer (Jasco, Hachioji, Japan).
The percentage of ABTS•+ inhibition was calculated using the following formula:

A (t = 0 min) − A (t = 6 min)
% ABTS inhibition = × 100, (2)
A (t = 0 min)

where:
A (t = 0 min) = absorbance of the blank sample (ABTS•+ solution in the absence of
tested samples: 0.70 ± 0.02);
A (t = 6 min) = absorbance of the vegetal extract (ABTS•+ solution in the presence of
tested samples).
The concentration of sample needed to scavenge 50% of the ABTS•+ free radical, or
the IC50 value, was determined by plotting radical scavenging activity against extract
concentration (IC—inhibitory concentration). The antioxidant activity of an extract is
inversely correlated with the IC50 value.

Antioxidant Activity Using FRAP Assay (Ferric Reducing Antioxidant Power Assay)
A modified FRAP assay was used to assess the ferric reducing capacity of plant
extracts [65]. The reduction of ferric iron (Fe3+ ) to ferrous iron (Fe2+ ) by antioxidants present
Plants 2022, 11, 2398 20 of 26

in the samples is how the assay determines the antioxidant potential. Blue coloration results
from the conversion of ferric iron (Fe3+ ) to ferrous iron (Fe2+ ).
Equal amounts of 0.1 g dry extracts were dissolved in 100 mL 50% ethanol for every
plant extract used in our study. Eight corresponding volumes of each obtained solution
were brought into volumetric flasks and adjusted to 10 mL by adding the same solvent as
above. An amount of 2.5 mL of each diluted solution was mixed with phosphate buffer
(pH 6.6, Sigma–Aldrich, Hamburg, Germany) and 2.5 mL K3 (FeCN)6 1% (Sigma–Aldrich,
Hamburg, Germany) before being heated to 50 ◦ C for 20 min. 2.5 mL trichloroacetic acid
(Sigma–Aldrich, Hamburg, Germany) was added to each sample. Furthermore, 2.5 mL of
distilled water and 0.5 mL FeCl3 0.1% (Sigma–Aldrich, Hamburg, Germany) were added to
2.5 mL of each of the resulting solutions, the samples being left thereafter idle for 10 min.
The change in the absorbance at 700 nm was measured relative to a blank sample obtained
by mixing 5 mL distilled water with 0.5 mL FeCl3 0.1%.
The antioxidant capacity was calculated using the IC50 (half of the antioxidant effect—
IC—effective concentration) value (mg/mL), which represents the solution concentration
for which the absorbance has a value of 0.5.
Different extract volumes were tested in order to reach the absorbance value of 0.5, due
to the variability of plant characteristics and the nonuniformity of phytochemical profiles
of plant extracts (experimental values closer to the target value result in more accurate
approximation—IC50 for y = 0.5). The optimized values have been set as mentioned above
in order to conduct an appropriate comparative study within the same technique and
between other methods of assessing the antioxidant activity.

4.5.2. In Silico Methods

Molecular Docking
Molecular docking simulations were performed for the identified phytochemicals to
assess the potential biological activities on sirtuin isoforms. Crystal structures of human
sirtuin 1 (PDB ID: 5BTR, 3.20 Å resolution [68]) and sirtuin 5 (PDB ID: 4HDA, 2.60 Å
resolution [69]) in complex with peptide substrates and activator resveratrol, and sirtuin 6
in complex with ADP-ribose and activator quercetin (PDB ID: 6QCD, 1.84 Å resolution),
and inhibitor catechin gallate (PDB ID: 6QCJ, 2.01 Å resolution) [21], respectively, were
retrieved from RCSB PDB database. Since there are experimentally determined structures
available for both SIRT6 activator and inhibitor polyphenolic derivatives, we chose to
perform docking experiments on both receptor structures, to discriminate between potential
activators and inhibitors.
The preparation of protein structures was performed with YASARA Structure [70],
and consisted in the removal of solvent molecule, excepting the structurally relevant water
molecules, correction of structural errors and protonation according to the physiological
pH (7.4). The structures were further optimized by minimization with AMBER ff14SB force-
field. The validation of the docking protocol was performed by docking the co-crystallized
ligands into the active and superposing the predicted pose with the experimentally deter-
mined conformation. The ligands used for validation also served as positive controls for
docking score comparisons [71,72].
Three-dimensional structures of the tested ligands were generated with DataWarrior
5.2.1 [73]. Ligands were minimized using MMFF94s+ forcefield and protonated at physio-
logical pH. The molecular docking algorithm used was AutoDock Vina v1.1.2, executed
within YASARA. The search space (22.5 Å × 22.5 Å × 22.5 Å) was centered around the
co-crystallized ligands within the binding sites and 12 docking runs were performed for
each ligand.
Docking results were retrieved as the binding energy (∆G, kcal/mol), predicted disso-
ciation constant (Kd, µM) and ligand efficiency (LE, ∆G\no. of heavy atoms) of the best
binding pose for each screened ligand. The conformations of the predicted protein–ligand
complexes and molecular interactions were analyzed using BIOVIA Discovery Studio
Plants 2022, 11, 2398 21 of 26

Visualizer (BIOVIA, Discovery Studio Visualizer, Version 17.2.0, Dassault Systèmes, 2016,
San Diego, CA, USA).

Binding Free Energy Calculations

Short molecular dynamics simulations (1 ns) were performed to estimate the free
energy of binding for the positive controls and one promising phytochemical, using the
Poisson–Boltzmann (MM/PBSA) method, excluding the entropic term. The simulations
of the selected protein–ligand complexes were carried out with YASARA Structure. The
simulation system was neutralized by adding Na and Cl ions at 0.9% concentration. Clashes
were removed by performing steepest descent and simulated annealing minimizations.
AMBER14 force field was used for the protein [74], GAFF2 [75] and AM1BCC [76] for
ligand and TIP3P for water. The cut-off for van der Waals forces was 8 Å [77], while the
electrostatic forces were treated using the Particle Mesh Ewald algorithm and no cutoff
was applied [78]. The integration of motions equations was performed with a multiple
timestep of 2.5 fs for bonded and 5 fs for non-bonded interactions at 298 K and 1 atm
(isothermal-isobaric ensemble) [79].

4.6. Statistical Analysis

Statistical analysis was implemented using the open source software R (R version
4.1.3., R Foundation for Statistical Computing, Vienna, Austria) [80]. The statistics were
performed on 5 replicates. Therefore, the application of robust inferential methods becomes
vital, especially as they have results with increased accuracy in the case of samples with
relatively small sizes [81]. As a means to simultaneously evaluate the effect of two factors,
Compound (with three levels: FL and TPC) and Sample (with two levels: common crop
and control crop in first analysis or with three levels in second analysis: common crop,
Bio crop and NPK crop) on a response variable named Concentration, we used two-way
robust ANOVA test for every plant product (peppermint and lemon balm) [82]. Statistical
significance is set to 0.05 (5%) and for post hoc analysis a Bonferroni adjusted alpha level
was used. Pearson statistical analysis was performed using IBM SPSS Statistics software
version 28.0 (IBM Corporation, Armonk, NY, USA). The correlation between antioxidant
activity and active principles from vegetal extracts was established by calculating the
Pearson correlation coefficient. The Pearson correlation results were interpreted both
mathematically and statistically. Interpretations were made after the mandatory application
criteria were met (normality of data sets, linearity, independence of measurements and
continuity of variables). Moreover, we tested the absence of outliers and we transformed by
logarithm in base 10 certain experimental data which did not follow a normal distribution,
so that they could be subjected to statistical tests. The significance level was set at 0.05.

5. Conclusions
Based on the present studies, we can consider that interventions in the cultivation
of medicinal plants can sometimes be beneficial in terms of generating a greater quantity
of plant product, but also in enriching the polyphenolic content. The phytosociological
cultivation of mint and melissa showed positive effects on the biosynthesis of polyphenolic
compounds. Fertilization with organic fertilizer, although not generating a larger quantity
of plant raw material, lead to clearly higher polyphenolic contents than in the batches
treated with chemical fertilizer. Polyphenols identified and quantified by FT–ICR MS and
UHPLC–MS supported the antioxidant activity of assessed plant extracts.
Molecular docking studies supported the hypothesis that the obtained extracts have
the potential to directly activate SIRT1, 5 and 6 through several polyphenolic compounds,
thus complementing the free radical scavenging activity with the potential stimulation of
endogenous antioxidant defense mechanisms.
Future phytosociological studies are needed to investigate the interrelationships be-
tween other types of medicinal species belonging to different genera and families.
Plants 2022, 11, 2398 22 of 26

Supplementary Materials: The following supporting information can be downloaded at: https://
www.mdpi.com/article/10.3390/plants11182398/s1, Figure S1: Entire mass spectra of mint obtained
on positive ionization; Figure S2: Chlorogenic acid (C16H18O9)—m/z is 355.10, ESI+; Figure S3:
Caffeic acid (C9H8O4)—m/z is 181.05, ESI+; Figure S4: Rosmarinic acid (C18H16O8)—m/z is 361.09,
ESI+; Figure S5: Isoquercitrin (C21H20O12)—m/z is 465.10, ESI+; Figure S6: Luteolin + Kaempferol
(C15H10O6)—m/z is 287.06, ESI+; Figure S7: Quercetin (C15H10O7)—m/z is 303.05, ESI+; Figure S8:
Ferulic acid (C15H10O6)—m/z is 195.07, ESI+; Figure S9: Entire mass spectra of lemon balm obtained
on positive ionization; Figure S10: Chlorogenic acid (C16 H18 O9 )—m/z is 355.10, ESI+; Figure S11:
Caffeic acid (C9H8O4)—m/z is 181.05, ESI+; Figure S12: Rosmarinic acid (C18H16O8)—m/z is 361.09,
ESI+; Figure S13: Isoquercitrin (C21H20O12)—m/z is 465.10, ESI+; Figure S14: Luteolin + Kaempferol
(C15H10O6)—m/z is 287.06, ESI+; Figure S15: Quercetin (C15H10O7)—m/z is 303.05, ESI+; Figure
S16: Ferulic acid (C15H10O6)—m/z is 195.07, ESI+; Figure S17: p-Coumaric acid (C9H8O3)—m/z is
165.05, ESI+; Figure S18: Rutin (C27 H30 O16 )—m/z is 611.16, ESI+; Figure S19: entire mass spectra
obtained on negative ionization; Figure S20: Chlorogenic acid (C16H18O9)—m/z is 353.09, ESI−;
Figure S21: Caffeic acid (C9H8O4)—m/z is 179.03, ESI−; Figure S22: Rosmarinic acid (C18H16O8)—
m/z is 359.08, ESI−; Figure S23: Isoquercitrin (C21H20O12)—m/z is 463.09, ESI−; Figure S24:
Luteolin + Kaempferol (C15H10O6)—m/z is 285.04, ESI−; Figure S25: Quercetin (C15H10O7)—m/z
is 301.04, ESI−; Figure S26: Ferulic acid (C15H10O6)—m/z is 193.05, ESI−; Figure S27: p-Coumaric
acid (C9H8O3)—m/z is 163.04, ESI−; Figure S28: Protocatechuic acid (C7H6O4)—m/z is 153.02,
ESI−; Figure S29: Rutin (C9H8O3)—m/z is 609.15, ESI−; Figure S30: entire mass spectra obtained on
negative ionization; Figure S31: Caffeic acid (C9H8O4)—entire chromatogram, m/z is 179.03, ESI−;
Figure S32: Caffeic acid (C9H8O4)—m/z is 179.03, ESI−; Figure S33: Chlorogenic acid (C16H18O9)—
m/z is 353.09, ESI−; Figure S34. Rosmarinic acid (C18H16O8)—m/z is 359.08, ESI−; Figure S35:
Isoquercitrin (C21H20O12)—m/z is 463.09, ESI–; Figure S36: Luteolin + Kaempferol (C15H10O6)—
m/z is 285.04, ESI−; Figure S37: Luteolin + Kaempferol (C15H10O6)—entire chromatogram, m/z
is 285.04, ESI−; Figure S38: Quercetin (C15H10O7)—m/z is 301.04, ESI−; Figure S39: Ferulic acid
(C15H10O6)—m/z is 193.05, ESI−; Figure S40: p-Coumaric acid (C9H8O3)—m/z is 163.04, ESI−;
Figure S41: Protocatechuic acid (C7H6O4)—m/z is 153.02, ESI−; Figure S42: Rutin (C9H8O3)—m/z
is 609.15, ESI−; Figure S43: A two–way interaction boxplot for polyphenols assessed in peppermint;
Figure S44: A two–way interaction boxplot for polyphenols assessed in lemon balm; Figure S45: A
two–way interaction boxplot for peppermint in relation to the type of fertilizer; Figure S46: A two–
way interaction boxplot for Lemon balm in relation to the type of fertilizer; Figure S47: Calibration
curve for ascorbic acid (vitamin C)—Antioxidant action in 50% Ethanol; Figure S48: Calibration
curve for trolox—Antioxidant action in 50% ethanol; Figure S49: Calibration curve for ferrous
sulfate—Antioxidant action in 50% ethanol; Figure S50: Superposition of predicted poses (purple) on
initial conformations (green). (a)—SIRT1-resveratrol; (b)—SIRT5–resveratrol; (c)—SIRT6–quercetin;
(d)—SIRT6–catechin gallate; Figure S51: Standard chromatogram; Table S1: Correlation coefficients
between TFL, TPC and antioxidant methodologies; Table S2: Predicted dissociation constants (Kd)
calculated using molecular docking experiments; Table S3: Predicted free energies of binding using
MM/PBSA calculations after 1 ns molecular dynamics simulations; Table S4: Calibration curve
concentration by level (expressed in µg/g) and purity (%). Table S5: Retention times.
Author Contributions: Conceptualization, E.A.L., A.B., A.M., M.G., D.P.M., O.T.O., D.L., R.B. and
C.E.G.; methodology, E.A.L., A.B., A.M., D.E.M., M.G., D.P.M., O.T.O., T.D.-I., L.E.D., M.L.P., L.C.,
G.M.N., D.L., R.B. and C.E.G.; software, E.A.L., A.B., A.M., M.G. and D.P.M.; validation, E.A.L., A.B.,
A.M., D.E.M., M.G., D.P.M., O.T.O., D.L., R.B. and C.E.G.; formal analysis, E.A.L., A.B., A.M., M.G.
and D.P.M.; investigation, E.A.L., A.B., A.M., M.G., D.P.M., O.T.O., D.L., R.B. and C.E.G.; resources,
E.A.L., A.B., A.M., M.G., D.P.M., O.T.O., D.L., R.B. and C.E.G.; data curation, E.A.L., A.B., A.M., M.G.,
D.P.M., O.T.O., D.L., R.B. and C.E.G.; writing—original draft preparation, E.A.L., A.B., A.M., M.G.,
D.P.M., O.T.O., D.L., R.B. and C.E.G.; writing—review and editing, E.A.L., A.B., A.M., M.G., D.P.M.,
O.T.O., D.L., R.B. and C.E.G.; visualization, E.A.L., A.B., A.M., M.G., D.P.M., O.T.O., D.L., R.B. and
C.E.G.; supervision, D.P.M., D.L. and C.E.G.; project administration, E.A.L. and C.E.G. All authors
have read and agreed to the published version of the manuscript.
Plants 2022, 11, 2398 23 of 26

Funding: The authors received financial support for the publication of this article from “Carol Davila”
University of Medicine and Pharmacy, Bucharest, Romania, “Publish not Perish” Grants, and collabo-
rated with the Faculty of Medicine and Pharmacy, Craiova and the Faculty of Chemical Engineering
and Biotechnologies, University of Politehnica, Gheorghe Polizu. The FT–ICR MS analyses on our
samples were possible due to European Regional Development Fund through Competitiveness Oper-
ational Program 2014–2020, Priority axis 1, Project No. P_36_611, MySMIS code 107066, Innovative
Technologies for Materials Quality Assurance in Health, Energy and Environmental—Center for In-
novative Manufacturing Solutions of Smart Biomaterials and Biomedical Surfaces—INOVABIOMED.
Institutional Review Board Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.

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