Chemical Composition and Preliminary Toxicity Evaluation of the Essential Oil from Peperomia circinnata Link var. circinnata. (Piperaceae) in Artemia salina Leach

Peperomia Ruiz and Pav, the second largest genus of the Piperaceae, has over the years shown potential biological activities. In this sense, the present work aimed to carry out a seasonal and circadian study on the chemical composition of Peperomia circinata essential oils and aromas, as well as to evaluate the preliminary toxicity in Artemia salina Leach and carry out an in silico study on the interaction mechanism. The chemical composition was characterized by gas chromatography (GC/MS and GC-FID). In the seasonal study the essential oil yields had a variation of 1.2–7.9%, and in the circadian study the variation was 1.5–5.6%. The major compounds in the seasonal study were β-phellandrene and elemicin, in the circadian they were β-phellandrene and myrcene, and the aroma was characterized by the presence of β-phellandrene. The multivariate analysis showed that the period and time of collection influenced the essential oil and aroma chemical composition. The highest toxicity value was observed for the essential oil obtained from the dry material, collected in July with a value of 14.45 ± 0.25 μg·mL−1, the in silico study showed that the major compounds may be related to potential biological activity demonstrated by the present study.

Peperomia Ruiz and Pav is the second largest genus of the Piperaceae family, containing about 1600 species [5], and is considered one of the 10 main genus rich in floristic plants species [6]. This genus species are endemic to the Amazon and the Andes, with distribution in tropical and subtropical regions around the world, although these species are more concentrated in the Americas, where there is the greatest habitat diversity, from the southern United States to Argentina and Chile [5]. In Brazil, there are around 162 species, In a previous study on the essential oil yield from P. circinnata Link var. circinnata [22], the authors obtained values of 1-2.8%, similar to those observed in this study. In addition, studies have related the maximum and minimum essential oils yields to the rainfall index as one of the factors which added to the period of seasonal collection [29][30][31][32].
The essential oil yields obtained in the months of November and March for the circadian study are shown in Table 2. The botanical material collection was carried out in two periods, evening (M) and afternoon (A). The material was dried by two processes: oven and lyophilization. It is observed that the essential oils' yields obtained from fresh (F), oven dried (D), and lyophilized (L) materials of collections carried out in the evening and afternoon did not show significant variations owing to the function of time (Table 2). P. circinnata Link var. circinnata essential oils obtained in the rainy season of march showed yields of 1.2-3.5%. For fresh samples collected at night, the best yield was 3.5%. In the period of years considered to have been without rain, the month of November (dry period) produced fresh samples which had the highest yields, as seen in Table 2, with the highest value being 5.6%. In this study, lyophilization was the technique that most influenced the lowest essential oil yields, with a variation in the yield of 1.2-1.8% for the month of March and 1.6% for November; according to Chua et al. [33], drying methods can influence mass yields and no method is 100% effective for dehydrating plants rich in essential oils. As observed by other authors [34][35][36][37], oven drying and lyophilization can change the samples' morphological characteristics in relation to being fresh or dried at room temperature, which can hinder the essential oils' extraction, affecting their mass yield and chemical composition. Evening, afternoon, fresh (F), oven drying (D), and lyophilization (L).
Seasonal variation was observed among the constituents identified in the aromas of the whole plant devoid of spikes in both fresh and dried samples (Table 5), as well as in the whole plant and spikes' fresh samples obtained from the November, January, March, and May collections. The mono and sesquiterpenes present in the whole plant samples from November showed similar levels in relation to the dry and fresh samples; in January the sesquiterpenes were 50% higher than the monoterpenes in the dry sample, while in the fresh sample the contents were similar, also presenting a higher concentration of phenylpropanoid elemicin (12.7%); in March the sesquiterpenes contents were approximately 15% higher in the dry sample, while in the fresh one the monoterpenes were superior (≈9.0%) to the sesquiterpenes. In May, sesquiterpenes were higher in the fresh samples' aromas (20%) and predominated in the dry (50%) compared to monoterpenes.
The relationship between the constituents identified in the aromas of the whole plant and the fresh materials' spikes can be seen in Table 5. The monoterpenes and sesquiterpenes showed similar levels in the months of November, January, and March for the whole plant, the same occurring in the spikes in the months of November and May; the greatest variation in the terpenes class occurred in spikes of March, 7% of sesquiterpenes and 62% of monoterpenes, in the whole plant occurred in May, but there was an inversion, that is, the sesquiterpenes (60%) were superior to the monoterpenes (3%). The presence of the phenylpropanoid class was represented by methyl-eugenol in spikes during the four months of collection (5.4-31.6%) and elemicin in the whole plant in January (12.7%) and in spikes in May (7.0%).
The analysis of essential oil in the circadian study can be seen in (Table 3); in general, 38 compounds were identified in all analyzed fractions, with the predominance of mycrene (4.7-12.1%), β-phellandrene (4.3-28.1%), β-elemene (2.7-10%), germacrene D (5.8-13%), cubebol (0-7.5%) elemol (0-15%), and elemicin with a range of (0-18.3%). P. circinnata whole plant devoid of spikes also revealed circadian variation on the chemical composition of fresh and dry samples, mainly in November. In March, there was no significant variation between monoterpenes and sesquiterpenes. The variation was clearly observed in the November collection, in which sesquiterpenes predominated over mono, mainly in the fresh evening sample (82%), ranging from 59-71% in the others. Phenylpropanoid elemicin only appeared in the month of March, in the afternoon collection (2.5 and 4.0%).
In Zoghbi et al.'s [22] study on P. circinnata Link var. circinnata essential oil, the highest concentrations were myrcene (12.2-31.2%) and β-phellandrene (17.5-25.4%); in Silva et al.'s [23] study, the highest concentrations were myrcene 8.3%, limonene 13.5%, cubebol 9.7%, and elemicin 11.5%. Other Peperomia species such as P. rotundifolia, P. pelucida, and P. macrostachya from the Amazon were found to contain major compounds, such as epi-α-bisabolol 15.9%, caryophyllene oxide 12.9%, myristicin 7.6%, aromatic compound 6.6%, and andlimonene 5.4% in P. macrostachya, dillapiole 55.3%, (E)-caryophyllene 14.3%, and carotol (8.1%) in P. pellucida, and decanal (43.3%) in P. rotundifolia [38]. Table 3. Chemical constituents obtained from the circadian study of P. circinnata Link var. circinnata (fresh (F), oven dried (D), lyophilized (L), evening period (EP), afternoon period (AP), rainy season (rs), and dry season (ds)). The concentration values of the compounds are (%).   RIC: retention index (on DB-5MS column); RIL: literature retention index (Adams [36]). Table 4. Seasonal variation on the chemical composition of P. circinnata Link var. circinnata essential oils in the months of July, September, November, January, March, and May, fresh (F) and oven dried (D). The concentration values of the compounds are (%).   The multivariate analysis PCA (Principal Component Analysis) ( Figure 1) and HCA (Hierarchical Cluster Analysis) of the chemical compounds identified in the essential oils different fractions from samples collected between March and November. The first PC1 component explains 43.4% whereas PC2 explains 19.7% of the variations, and the two components add up to 63.1% of variance ( Figure 1). The HCA analysis, considering the Euclidean distances and complete bonds (Figure 2), confirmed the formation of two distinct groups. Group 1, with 32.35% similarity, is formed by samples collected from March to November and dried in an oven, plus a sample of fresh P. circinnata Link var. circinnata collected in March. The multivariate analysis PCA (Principal Component Analysis) ( Figure 1) and HCA (Hierarchical Cluster Analysis) of the chemical compounds identified in the essential oils different fractions from samples collected between March and November. The first PC1 component explains 43.4% whereas PC2 explains 19.7% of the variations, and the two components add up to 63.1% of variance (Figure 1). The HCA analysis, considering the Euclidean distances and complete bonds (Figure 2), confirmed the formation of two distinct groups. Group 1, with 32.35% similarity, is formed by samples collected from March to November and dried in an oven, plus a sample of fresh P. circinnata Link var. circinnata collected in March. Group 2 with 21.13% similarity, shown in Figure 2, was formed by samples collected from May to November without drying treatment (fresh samples). The compounds that characterized group 1 were elemecin, β-phellandrene, germacrene D-4-ol, cubebol, myrcene, β-pineneand, and α-pinene, whereas group 2 was formed by the compounds β-caryophyllene, δ-cadinene, α-muurolene, germacrene D, β-elemene, β-copaene, elemol, and β-ylangene. We also observed that in the present study, seasonality was not the main variable for the groups' separation, but instead it was the treatment of samples before extraction, which may mean that pre-treatment can be a variable for maintaining the chemical composition without generating losses of compounds by volatilization or degradation. Group 2 with 21.13% similarity, shown in Figure 2, was formed by samples collected from May to November without drying treatment (fresh samples). The compounds that characterized group 1 were elemecin, β-phellandrene, germacrene D-4-ol, cubebol, myrcene, β-pineneand, and α-pinene, whereas group 2 was formed by the compounds β-caryophyllene, δ-cadinene, α-muurolene, germacrene D, β-elemene, β-copaene, elemol, and β-ylangene. We also observed that in the present study, seasonality was not the main variable for the groups' separation, but instead it was the treatment of samples before extraction, which may mean that pre-treatment can be a variable for maintaining the chemical composition without generating losses of compounds by volatilization or degradation.

Multivariate Analysis of the Aroma Chemical Composition
Principal component analysis was applied to the aroma of P. circinnata Link var. circinnata's whole part and its spikes, and in Figure 3 we observe the principal components analysis, in which the first component explains 23.3% of the variations, whereas the second component explains 18.2%, and the sum of the variances explains 41.1%. Considering the Euclidean distances and complete bonds (Figure 4), in the HCA analysis, the formation of five groups is observed, with group 1 being formed by the samples Nov-D, Mar-D, Nov-F, Jan-F, May-F, and May-D, showing a 32.35% similarity degree, and being characterized by β-caryophyllene, germacrene D, β-elemene, cubebol, γ-muurolene, terpinolene, germacrene D-4ol, β-copaene, δ-cadinene, α-pinene, elemol, and β-pinene compounds. Group 2 (Figure 3), was characterized by the grouping of S-Nov-F, S-Jan-F, and S-May-D samples, showing a similarity of 36.39%, and was characterized by cis-nerolidol and elemecin compounds. Group 3 (Figure 3) was formed only by the Jan-D sample, which in the principal component analysis was characterized by β-cedrene, (E)-muurola-4(14),5diene, and β-himachalene. Groups 4 and 5 ( Figure 3) were formed by Mar-F and S-Mar-F samples, showing a 20.50% similarity degree for the two samples, being characterized by, cis-muurola-5-en-4-α-ol and douca-4(11),8-diene, and β-phellandrene, n-decanal, myrcene and methyl eugenol compounds, respectively.

Multivariate Analysis of the Aroma Chemical Composition
Principal component analysis was applied to the aroma of P. circinnata Link var. circinnata's whole part and its spikes, and in Figure 3 we observe the principal components analysis, in which the first component explains 23.3% of the variations, whereas the second component explains 18.2%, and the sum of the variances explains 41.1%. Considering the Euclidean distances and complete bonds (Figure 4), in the HCA analysis, the formation of five groups is observed, with group 1 being formed by the samples Nov-D, Mar-D, Nov-F, Jan-F, May-F, and May-D, showing a 32.35% similarity degree, and being characterized by β-caryophyllene, germacrene D, β-elemene, cubebol, γ-muurolene, terpinolene, germacrene D-4ol, β-copaene, δ-cadinene, α-pinene, elemol, and β-pinene compounds. Group 2 (Figure 3

Multivariate Analysis of the Circadian Study Chemical Composition
In the circadian study, the essential oils of P. circinnata Link var. circinnata collected in the evening and afternoon, in the winter and summer, when applying principal component analysis (PCA), it is observed that PC1 explained 49.4% and PC2 explained 29.8% of the analyzed variables, while the sum of the variances PC1 and PC2 added up to 79.2% ( Figure 5). Figure 6 brings the Hierarchical Cluster Analysis (HCA); the formation of two

Multivariate Analysis of the Circadian Study Chemical Composition
In the circadian study, the essential oils of P. circinnata Link var. circinnata collected in the evening and afternoon, in the winter and summer, when applying principal component analysis (PCA), it is observed that PC1 explained 49.4% and PC2 explained 29.8% of the analyzed variables, while the sum of the variances PC1 and PC2 added up to 79.2% ( Figure 5). Figure 6 brings the Hierarchical Cluster Analysis (HCA); the formation of two groups can be observed, group 1 being formed by the grouping of samples collected in the evening and afternoon, fresh and dried in greenhouses as F-EP-rs, D-EP-rs, D-EP-ds, D-AP-ds, L-AP-ds, F-AP-rs, D-AP-rs, and L-AP-rs. In Figure 5, we can see that group 1 was characterized by the compounds that had the highest weights for analysis, such as β-caryophyllene, elemecin, mircene, β-phellandrene, β-pineneand, and α-pinene. Group 2 ( Figure 6) was formed by agglutination of L-EP-rs, F-EP-ds, F-AP-ds, and L-EP-ds samples. In Figure 5, using PCA, group 1 was characterized by the presence of the components β-copaene, elemol, δ-cadinene, β-elemene, and germacrene D, and group 2 was characterized by α-pinene, β-pinene, β-phellandrene, mircene, elemecin, and β-caryophyllene. In Pirbalouti's [40] work, the increase in drying temperature decreased the concentrations of α-pinene, sabinene, β-myrcene, and β-phellandrene in the basil essential oil.

Cytotoxicity Bioassay in Artemia Salina
In the control group tests there was no mortality; therefore, the use of DMSO is viable as a solvent for the assay. LC 50 values were calculated by converting the percentage of larvae mortality into probits, thus making it possible to trace the equation as a function of concentration values on a logarithmic scale (Table 6). Furthermore, studies have shown that there is a strong correlation between in vitro toxicity results using A. salina and in vivo study using natural products [41,42].
Toxicity tests in A. Salina performed using Hyptis suaveolens (L.) Poiteau (Lamiaceae) essential oil [45] presented LC 50 values similar to those obtained in the present work, whereas the Garcinia mangostana essential oil obtained LC 50 of 1.70 µg·mL −1 and 5.15 µg·mL −1 for leaves and stem [46], and Ferulago trifida had LC 50 1.1 ± 0.3 µg·mL −1 [47]; these toxicities were higher than those presented by P. circinnata Link var. circinnata essential oils. Essential oils rich in phenylpropanoids such as cloves, demonstrated LC 50 value of 0.5993 ± 0.0464 µg·mL -1 [48], which is higher than the tests of the major substances tested separately; this may be related to the synergistic effect of the substances present in the essential oil [49][50][51]. According to Radulović et al. [52], essential oils that have high toxicity values must be carefully managed to avoid intoxication. In a study carried out with three species of Peperomia, the authors obtained LC 50 results of 1.9 ± 0.1 µg·mL −1 for P. rotundifolia essential oil, 2.4 ± 0.5 µg·mL −1 for P. pellucida extract, and 9.0 ± 0.4 µg·mL −1 for P. macrostachya essential oils.

In Silico Evaluation of Interaction with AChE
Previous studies have successfully reported the use of in silico approaches to evaluate the interaction of naturally occurring compounds that have molecular targets of pharmacological and toxicological interest [53][54][55][56]. For this reason, molecular docking was used to investigate the interactions established between β-elemene and elemicin with AChE. This enzyme has been reported as a target for A. salina [21,57]. The binding mode and interactions established in the complex can be seen in Figure 7.

In Silico Evaluation of Interaction with AChE
Previous studies have successfully reported the use of in silico approaches to evaluate the interaction of naturally occurring compounds that have molecular targets of pharmacological and toxicological interest [53][54][55][56]. For this reason, molecular docking was used to investigate the interactions established between β-elemene and elemicin with AChE. This enzyme has been reported as a target for A. Salina [21,57]. The binding mode and interactions established in the complex can be seen in Figure 7.  Before performing the docking of the molecules of interest, it was necessary to validate the protocol described in the methodology. To develop the methodology, we first tried to reproduce the binding mode of the crystallographic ligand performing its redocking. For this, the ligand of the PDB 4M0E was deleted [58] and then it was redocked. To assess the binding mode's reproducibility, the ligand interacting conformation was evaluated by comparing the redocked structure with the crystal structure. The evaluation of the obtained complexes was carried out using the root-mean-square deviation RMSD between the ligands. According to the literature, for the docking protocol to be validated, the RMSD between the redocked and the crystallographic ligand must be less than 2 Å [59][60][61][62]. In our results, an RMSD of 1.42 Å was obtained. In Figure 7, it is possible to visualize the compounds overlapping. After protocol validation, the docking between β-elemene and elemicin was performed.
The MolDock Score obtained was −91.61 Kcal/mol for the complex formed by βelemene and −90.19 Kcal/mol for the system established with elemicin. In these binding poses the ligands were able to form an interaction with residues from the enzyme catalytic cavity. These interactions are able to favor the compounds inhibitory capacity.
The AChE binding cavity is formed by three subsites, the anionic subsite (Trp86, Tyr133, Tyr337, and Phe338), acyl pocket (Phe295 and Phe297), and oxyanion hole (Gly121, Gly122, and Ala204) [63,64]. In Figure 8A,B, it shows that the two ligands are able to interact with residues present in the anionic subsite. With residues from this subsite, the β-elemene compound interacted with Tyr337 and Phe338 through hydrophobic interactions of the pi-alkyl type. The elemicin ligand interacted with Tyr337 through hydrogen bonds. Besides these, other interactions were established with the ligands in the binding pocket. The βelemene also interacted with Tyr124, Tyr72, Trp286, and Tyr341. All these interactions were hydrophobic of the pi-alkyl type. Elemicin formed pi-pi type hydrophobic interactions with Tyr341 and Trp286, as well as hydrogen bonds with Tyr124, Figure 8A,B.
The AChE binding cavity is formed by three subsites, the anionic subsite (Trp86, Tyr133, Tyr337, and Phe338), acyl pocket (Phe295 and Phe297), and oxyanion hole (Gly121, Gly122, and Ala204) [63,64]. In Figure 8A,B, it shows that the two ligands are able to interact with residues present in the anionic subsite. With residues from this subsite, the β-elemene compound interacted with Tyr337 and Phe338 through hydrophobic interactions of the pi-alkyl type. The elemicin ligand interacted with Tyr337 through hydrogen bonds. Besides these, other interactions were established with the ligands in the binding pocket. The β-elemene also interacted with Tyr124, Tyr72, Trp286, and Tyr341. All these interactions were hydrophobic of the pi-alkyl type. Elemicin formed pi-pi type hydrophobic interactions with Tyr341 and Trp286, as well as hydrogen bonds with Tyr124, Figure  8A,B.

Collection of Botanical Material for Seasonal and Circadian Study
P. circinnata Link var. circinnata collections occurred bimonthly, from July to May, in the evening, always on the 15th day at 8 am in Belém, Pará, and the samples were removed

Collection of Botanical Material for Seasonal and Circadian Study
P. circinnata Link var. circinnata collections occurred bimonthly, from July to May, in the evening, always on the 15th day at 8 am in Belém, Pará, and the samples were removed from the mango tree trunks near the Emílio Goeldi Zoo and Botanical Park. In November and March, collections were carried out in the evening and afternoon (8 am and 5 pm) for the circadian study. This specimen was identified by comparison with an authentic voucher (MG 172736) deposited in the Emılio Goeldi Museum herbarium, city of Belém, Pará state, Brazil.

Processing of Botanical Material
Whole plants devoid of spikes were divided into two parts; the fresh material was cut into small parts and subjected to the hydrodistillation process. The remainder was dried in an air circulation oven at room temperature for five days, then ground, homogenized, weighed, and subjected to hydrodistillation. Drying for the circadian study was achieved by two processes: oven (ventilation) and lyophilization.

Extraction Methods Hydrodistillation
For the essential oil extraction process in circadian and seasonal studies, 40 g of fresh and dry sample from P. circinnata Link var. circinnata were dried in an air circulation oven and then subjected to hydrodistillation. The same proportion of water in relation to plant material was used, according to the methodology described by [53,65].

Simultaneous Distillation-Extraction
For aroma extraction, 10 g of sample from P. circinnata Link var. circinnata was used, then mixed with water (20 mL) and subjected to simultaneous distillation-extraction (SDE) for 3 h, using a Chrompack Micro-Steam Distillation Extractor (Likens-Nickerson) and pentane (2 mL) as organic mobile phase, as described by [66].

Identification of Chemical Constituents
The chemical composition of P. circinnata Link var. circinnata essential oils and aromas was analyzed by Gas Chromatography coupled with Mass Spectrometry, using a Thermo DSQ-II system equipped with a DB-5MS silica capillary column (30 m × 0.25 mm; 0.25 µm) with temperature program: 60-240 • C, using gradient of 3 • C/min; injector temperature: 240 • C; carrier gas: helium (linear velocity of 32 cm/s, measured at 100 • C); splitless injection flow (0.1 mL of a 2:1000 sol. of n-hexane); temperature of ion source and other parts at 200 • C. The quadrupole filter swept in the range of 39 to 500 daltons every second. Ionization was achieved by the electronic impact technique at 70 eV. Volatile components identification was based on the linear retention index (Kováts Index) calculated in relation to the retention times of a homologous series of n-alkanes (C 8 -C 40 ) according Van den Dool and Kratz [67] and on the fragmentation pattern observed in the mass spectra, by comparison in the data system and literature libraries [39,68]. Quantitative data regarding the volatile constituents were obtained by peak-area normalization using a FOCUS GC/FID, as previously reported by our research group [69].

Preliminary Toxicity Bioassay with Artemia Salina Leach
For the toxicity tests, the sample with the highest mass yield was selected. The preliminary toxicity bioassay test of P. circinnata Link var. circinnata essential oil in A. salina Leach was performed as described in the literature [57,70,71]. The essential oil was prepared at concentrations of 100, 50, 20, 10, 5, and 1 µg·mL −1 were used, from fresh and dry samples obtained in the seasonal study in the months of July, September, November, January, March, and May. A total of ten Artemia salina larvae were added to each test flask with the aid of automatic micropipettes. Brine water (artificial) and DMSO were used as solvents with a 95:5 ratio. In the control group and the positive group with lapachol, the same solvent was used for the samples and larvae under the same conditions as the bioassay. After 24 h of contact between the larvae and the sample solution, the dead larvae were counted (in each concentration), and the mortality rate and the IC 50 value were calculated using the Probitos statistical method. All the experiments were performed in triplicate (n = 3).
We used the molecular method to evaluate the compounds interaction mode with Acetylcholinesterase (AChE). For this we used the Molegro Virtual Docker (MVD) 5.5 software [74], and the crystal structure used as a molecular target can be found in the Protein Data Bank (http://www.rcsb.org, accessed on 20 May 2021) using the ID: 4M0E [58].
The MolDock Score (GRID) scoring function was used with Grid resolution of 0.30Å and 5Å radius encompassing the entire connection cavity. The MolDock SE algorithm was used with number of runs equal to 10, 1500 max interactions, and max population size equal to 50. The maximum evaluation of 300 steps with neighbor distance factor equal to 1 and energy threshold equal to 100 was used during the molecular docking simulation.

Statistical Analysis
Multivariate analysis was performed according to the methodology described by [69,75], where Minitab 17 ® software (free version, Minitab Inc., State College, PA, USA) was used. The variables were the essential oils' chemical constituents. The raw data were first standardized to have the same "weight". The Principal Component Analysis (PCA) was obtained using the software configuration "correlation" of the matrix type. In the Hierarchical Cluster Analysis (HCA) of the samples, the Euclidean distance options were used for distance measurement and complete connection for connection method.

Conclusions
The highest essential oil yield from the seasonal analysis of P. circinnata Link var. circinnata during the study period was found in the fresh plant, especially in July, that is, in the dry season, which may mean that low humidity contributes to oil production. Multivariate analysis allowed to observe the similarities and differences between the chemical compositions in the different periods studied, showing that, according to the period and time of collection, there is a qualitative and quantitative change in the chemical composition. In the circadian study of the months of November and March, there were no significant variations in oil yield in the evening and afternoon collections. The essential oils obtained from fresh and dry plants showed a quantitative difference, in relation to the more volatile constituents (monoterpenes). Seasonal variation can be seen in relation to the presence of the phenylpropanoid elemicin in the months of July and January; as well as the oxygenated sesquiterpene elemol. These qualitative and quantitative variations of the oil are affected by seasonality and, consequently, are reflected in the biological activities evaluated, as at all concentrations we can observe that there was a low LC50 representing a potential biological activity of the samples. In the in silico study, it was observed that in the complex formed between AChE-β-elemene and AChE-elemicin, the interactions formed had residues present in the anionic subsite of the enzyme, in addition to interactions with other residues of the enzyme. Most of these interactions were hydrophobic and helped to maintain the systems formed by molecular interactions.