BioMed Research International

BioMed Research International / 2021 / Article

Research Article | Open Access

Volume 2021 |Article ID 9929805 | https://doi.org/10.1155/2021/9929805

Jéssica C. Andrade, Álefe B. Monteiro, Humberto H. N. Andrade, Thallita K. S. N. Gonzaga, Pablo R. Silva, Danielle N. Alves, Ricardo D. Castro, Mayara S. Maia, Marcus T. Scotti, Damião P. Sousa, Reinaldo N. Almeida, "Involvement of GABAA Receptors in the Anxiolytic-Like Effect of Hydroxycitronellal", BioMed Research International, vol. 2021, Article ID 9929805, 17 pages, 2021. https://doi.org/10.1155/2021/9929805

Involvement of GABAA Receptors in the Anxiolytic-Like Effect of Hydroxycitronellal

Academic Editor: Bogdan Tamba
Received07 Mar 2021
Accepted03 Jun 2021
Published17 Jun 2021

Abstract

Hydroxycitronellal (HC) is a monoterpene present in essential oils of aromatic plants of different species, obtained from semisynthesis of citronellal, and is widely used as a fragrance in cosmetics. The objective of this work was to evaluate the possible anxiolytic-like activity of HC and its possible mechanism of action using in vivo and in silico methodologies. Swiss male mice (Mus musculus) were treated with HC (12.5, 25, and 50 mg/kg, i.p.) and subjected to the rota rod, elevated plus maze, and open field tests. No significant impairments were observed in the rota rod tests for the motor activity of the animals treated with HC at 12.5, 25, and 50 mg/kg, i.p., indicating no myo-relaxing or sedative effects. In the elevated plus maze, HC (in the three doses) induced significant increases in the percentage of entries (respectively, 34.8%, 33.8%, and 38.6%) and in the length of stay (respectively, 49.9%, 56.1%, and 57.0%) in the open arms of the EPM, as well as the number of crossings in the open field tests. The mechanism of action of the compound’s anxiolytic-like activity can be attributed to the involvement of GABAA receptors, and this interaction was observed in in vivo and in silico studies. For HC, the results suggest anxiolytic-like effects, possibly via modulation of the GABAergic system. The use of natural products to treat anxiety can become an alternative to existing synthetic products.

1. Introduction

Anxious behavior is part of the normal spectrum of human experience. In certain situations, all people in life experience anxiety, especially when faced with some warning of imminent danger. This reaction allows us to escape from dangerous situations, as well as to improve our response in the face of adverse conditions when imposed by the environment [1]. If the risk response is emotionally disproportionate to the situation that triggers it, anxiety becomes a disorder [2].

Inherited genetic, neurobiological, environmental, and traumatic experiences can trigger pathologically anxious behavior. Anxious disorders are a clinical condition in which anxiety is the primary symptom and does not originate in other disorders, such as depression [3]. According to the World Health Organization, the proportion of the population who present some type of anxiety disorder in the world is 3.6%, that is, 256 million people, being more common in women (4.6%) than in men (2.6%) [4].

Pathological anxiety is treated with anxiolytic agents, which are substances that act on the central nervous system (CNS), resulting in changes in behavior, perception, thoughts, and emotions. They are recommended for people who suffer from emotional and psychological disorders that affect the functioning of the mind [5].

Benzodiazepines (BZDs) are a class of substances presenting anxiolytic effects and, due to their wide therapeutic window, high therapeutic efficacy. These drugs act through GABAA ionotropic receptors, intensifying inhibitory neurotransmission. Clinically, diazepam (DZP) is one of the most frequently used BZDs, and (similar to other BZDs) sedation is one of its more evident adverse reactions; it directly affects locomotor activity and compromises the quality of life of the user [6, 7].

Alternatives are needed to develop anxiolytics which possess fewer adverse reactions, possibly using medicinal plants, since they are an excellent source of bioactive substances which can present a great influence on health [8]. Medicinal plants with psychoactive activity present important effects on consciousness, emotions, and cognition, and due to these effects, they are used for many purposes. Pharmacological studies involving medicinal plants, especially aromatic ones, which present activity on the CNS, have helped to promote our understanding of the neurochemical base of behavioral disorders, making it a favorable field for the development of new drugs [9, 10].

Essential oils (EO) are odorous substances [11]. Formed in plant secondary metabolism, they act as a form of protection against predatory attacks, to attract pollinators, and have many other activities. The great structural variety of substances present in EOs is one of the factors responsible for their various pharmacological activities, including anxiolytic [12], antidepressant [13], anticonvulsant [14, 15], and antinociceptive effects [1620]. Some of these activities are attributed to the intensification of GABAergic transmission due the interaction of monoterpenes with GABAA receptors [21].

Hydroxycitronellal (HC) is a monoterpene present in essential oils of the most diverse genera of aromatic plants, yet little reported in the literature regarding its pharmacological effects. This monoterpene can be obtained from another monoterpene and citronellal, a metabolite of plant origin that already has several pharmacological activities proven in the literature, such as analgesic [22], anxiolytic [23], and anticonvulsant [24] activities. In view of the promising activity of one of its precursors (citronellal) in the CNS, the present study is aimed at evaluating the anxiolytic effect of HC and evidence of modulation of the GABAA receptor with acute administration in vivo and in in silico trials.

2. Materials and Methods

2.1. Animals

Swiss mice (Mus musculus), albino adult male, weighing between 25 and 35 g, approximately 3 months old, kept under temperature control (°C), with free access to water and feed, and a 12-hour light/dark cycle were used for all experimental protocols. The animals came from the Animal Production Unit (APU) of the Pharmaceuticals and Medicines Research Institute (IPeFarm) of the Federal University of Paraíba. All experimental procedures were previously approved by the CEUA-Ethics Committee on the Use of Animals at UFPB, under the certificate No. 1854110719.

2.2. Drugs

HC was purchased from Sigma-Aldrich® ChemicalCo (St. Louis, MO, USA). Diazepam and flumazenil were donated by the Brazilian pharmaceutical laboratory, Cristália-Produtos Químicos Farmacêuticos, LTDA (Itapira, SP, BR). All substances were diluted in saline and intraperitoneally administered (i.p.) at a total volume of 0.1 mL/10 g. HC was initially emulsified with Tween 80 (0.5%) in 0.9% saline. The control group received the vehicle (Tween 80-0.5% in 0.9% saline).

2.3. In Vivo Testing
2.3.1. Estimate of Acute Toxicity of Hydroxycitronellal

The acute toxicity tests were performed according to the OECD “Guidelines for testing of chemicals” n. 423/2001with modifications. Swiss mice, three females per group, including the control, were subjected to single doses of 2000 and 300 mg/kg of HC. The control group was treated with intraperitoneally. After administration, observations were made at 30 min, 1 h, 2 h, and 4 h and then once daily until the fourteenth day.

2.3.2. Rota Rod

The rota rod methodology assesses motor impairment in animals after administration of substances with potential CNS activity. The animals were exposed to the apparatus 24 h before the test, and the animals managing to stay on the rotating bar (at 10 rpm) for a period of 1 minute were selected for testing. These preselected animals () were treated (i.p.) with vehicle (control group: Tween 80-0.5%), diazepam (4 mg/kg), administered 30 min before the start of the test, or HC (12.5, 25, and 50 mg/kg). At 30, 60, and 120 minutes, the animals were placed on the rotating bar to assess time performance. For each animal, the time spent on the rotating bar was recorded for 3 minutes [25, 26]. The doses of HC were defined from the acute toxicity study and previous studies [27, 28].

2.3.3. Elevated Plus Maze Test

Groups of mice were used (). Substances, vehicle (control group: Tween 80-0.5%), diazepam (1 mg/kg), or HC (12.5, 25, and 50 mg/kg) were administered 30 min before the start of the test, intraperitoneally. After 30 minutes, each animal was placed individually on the central platform of the device, facing an open arm. The observed behavioral parameters were the number of entries and length of stay (in seconds) in the open arms and closed. An entry was counted only if the animal had four legs outside of the central line of the labyrinth. Each animal remained for a time of 5 min in the maze [29].

2.3.4. Open Field Test

The animals were submitted to the open field test and evaluated for a period of 5 minutes. For the experimental procedure, groups of 8 mice were used. HC (12.5, 25, 50 mg/kg), vehicle (control group: Tween 80-0.5%), and diazepam (1 mg/kg) were administered intraperitoneally, 30 min before the start of the test. After treatment (30 minutes), each animal was individually submitted to the device. The total number of quadrants covered (crossings), head rearing, and time spent on grooming was recorded [30].

2.3.5. Involvement of GABAergic Receptors in Anxiolytic Activity

This test was carried out with the aim of evaluating the possible involvement of GABAA receptors in the anxiolytic effect of the substance. The animals were divided into three pretreated groups (), vehicle (control group: Tween 80-0.5%), diazepam (1 mg/kg), and HC (12.5 mg/kg), 30 min before the start of the test. 20 min before starting treatments, all groups were pretreated with flumazenil (10 mg/kg), a GABAA receptor antagonist. Then, the animals were submitted to the elevated plus maze test. The observed behavioral parameters were number of entries and length of stay (in seconds) in the open arms. An entrance was counted only if the animal had four legs in one of the two open arms of the labyrinth [31].

2.4. In Silico Testing
2.4.1. Docking Consensus

The HC structure was obtained in (.sdf) format through ChemAxom (http://www.chemaxon.com). The α subunit of the GABAA receptor, under the code PDB ID 6HUJ, was obtained from the Protein Data Bank (PDB) (http://www.rcsb.org/). The ChemAxon (http://www.chemaxon.com) Standardizer Software JChem 14.9.1.0, 2014, was used to expose the HC structure, add hydrogens, perform aromatic shape conversion, outline the molecular graph in 3D, and generate compounds in the .sdf format [32].

Docking was performed using five different scoring functions (Molegro Virtual Docker (MVD), Gold 5.6.2, AutoDockVina (Vina), AutoDock 4.2.6. (AD4), and Plants). The water molecules were removed from the crystalline structure, and the mean square root deviation (from the “Root Mean Square Deviation” (RMSD)) of the poses was calculated, indicating the degree of docking reliability. The consensus strategy consisted of selecting predicted binding affinity values greater than the crystallographic ligands in at least three docking programs. The results were viewed using the Molegro Virtual Docker v.6.0.1 (MVD) software [33] and the Discovery Studio 2019 (https://www.3dsbiovia.com/products/collaborative-science/biovia-discovery -studio/visualization-download.php).

2.4.2. Molecular Dynamics Simulations

The GROMACS 5.0 software was used to perform molecular dynamics simulations [34]. Ligand topology was prepared using the ATB topology generator (https://atb.uq.edu.au/) [35, 36] and applying the GROMOS96 54a7 force field. Protein topology was also prepared using the GROMOS96 54a7 force field in GROMACS. Molecular dynamics simulation was performed using the SPC water model with a point charge in a cubic box [37]. The system was neutralized with the addition of ions (Cl- and Na+) and balanced at 300 K using the V-rescale algorithm at 100 ps, represented by NVT (constant number of particles, volume, and temperature), followed by equilibrium at 1 atm pressure using the Parrinello-Rahman algorithm-NPT (constant number of particles, pressure, and temperature) up to 100 ps. The MD simulations were performed in 5,000,000 steps at 10 ns. The mean square root displacement (RMSD) of all Cα atoms was calculated in relation to the starting structures. Residual fluctuations (RMSF) were also analyzed to understand the role of residues near the receptor binding site. The RMSD and RMSF graphs were generated in the Grace software (http://plasma-gate.weizmann.ac.il/Grace/), and the protein and ligands were visualized in UCSF Chimera [38].

2.4.3. Pharmacokinetic Predictions

Pharmacokinetic predictions (available for free) were obtained from electronic platforms: SwissADME (Swiss Institute of Bioinformatics, Switzerland) and Xenosite (Washington University of Medicine, United States). For predictive models interfacing, it was necessary that the structures were in the smile format, being generated by the Chemdraw Ultra 12.0 software [39].

2.4.4. Statistical Analysis

The results obtained in the in vivo experiments were analyzed using the software and one-way analysis of variance (ANOVA), followed by the Tukey test to compare the means. Data were expressed as (standard error of the mean), and a confidence level of 5% was adopted.

3. Results

3.1. In Vivo Testing
3.1.1. Estimate of Acute Toxicity of Hydroxycitronellal

With administration of HC at a dose of 2000 mg/kg, i.p., all animals died, making it necessary to decrease the dosage, as determined by the OECD (2001). HC was then administered at a dose of 300 mg/kg, i.p., and did not cause the animals to die. In view of the results, it was the estimated LD50 of the tested substance (HC) at 500 mg/kg. Using this result, to conduct pharmacological tests in vivo, we opted for HC in doses 12.5, 25, and 50 mg/kg, since doses below the LD50 value present a lower probability of being toxic.

3.1.2. Rota Rod

After administration of HC (i.p.) at doses of 12.5, 25, and 50 mg/kg, there were no significant differences in the length of stay of the animals on the rotating bar (tested after 30, 60, and 120 minutes) in relation to the control group (Figure 1). The animals in the DZP group did not remain on the rotating bar at the evaluated times.

3.1.3. Elevated Plus Maze Test

The results presented in Figure 2(a) demonstrate that the animals treated with HC at 12.5 (), 25 (), and 50 () mg/kg significantly increased the number of entries into the open arms of the labyrinth, in relation to the control group (), by 34.8%, 33.8%, and 38.6%, respectively. The diazepam-treated group also significantly increased the number of entries (63.5%) compared to the control.

The results obtained for the animals’ permanence in the open arms are shown in Figure 2(b). HC at the dose of 12.5 (), 25 (), and 50 () mg/kg significantly increased the animals’ permanence time in the open arms of the labyrinth, respectively, by 50.0%, 56.1%, and 57.0% compared to the control group (). The diazepam administered group () also presented significant results, increasing the animals’ permanence in the open arms of the device by 70.4% compared to the control group.

Figure 2(c) shows the results of the number of entries, of the animals, in the closed arms of the labyrinth. The animals treated with HC at doses of 12.5 (), 25 (), and 50 () showed significant differences when compared to the control group (); that is, the animals entered less into the closed arms of the labyrinth. The group treated with DZP also showed significant results, with a decrease in the number of entries in the closed arms ().

As for the length of stay in the closed arms, the animals treated with HC at doses of 12.5 (), 25 (), and 50 () exhibited significant differences when compared to the control group (); that is, the animals spent less time in the closed arms of the labyrinth. The group treated with DZP also showed significant results, with a decrease in the number of entries in the closed arms ().

3.1.4. Open Field Test

As to the animal ambulation behavior in the open field tests, the results are shown in Figure 3(a), and it was noticed that there was a significant increase in the movement of animals treated with HC at 12.5 (), 25 (), and 50 () mg/kg, respectively, by 71.5%, 71.0%, and 66.5% compared to the control group (). The DZP group () increased the animals’ ambulation by 67.9% when compared to the control group.

Figure 3(b) presents the results obtained for rearing. It can be observed that the HC groups at 12.5 (), 25 (), and 50 () mg/kg expressed a significant increase in head rearing behavior of 89.5%, 85.8%, and 80.7%, respectively, when compared to the control group (). The DZP group () increased this same behavior by 83.4%.

The results obtained for the grooming parameter can be seen in Figure 3(c). It is noticed that there was a significant difference in grooming time only in the group treated with HC at a dose of 25 mg/kg (), decreasing by 50.1% in relation to the control group (). In the group treated with DZP (), the decrease was 99.0%. The other doses of HC presented no significant differences in relation to the control group.

3.1.5. Effect of GABAergic Neuromodulation on the Anxiolytic Effects of HC

The results of Figure 4(a) (number of entries in the open arms of the EPM) reveal that the flumazenil + HC 12.5 group () presented a lower number of entries, at 12.7%, less than presented by HC (at 34.8%), and at a dose of 12.5%, when administered without the antagonist. The antagonist when administered with DZP () also reduced the number of entries to the open arms, yielding a percentage of 8.5%, which was less than that presented when DZP was administered alone (), at 63.5%. These results were not significant when compared to the control group ().

Figure 4(b) presents the results for the time spent by animals in the open arms of the EPM. The animals in the group treated with HC at 12.5% presented a permanence time of 49.9% (), this falling to 25.3% (), after pretreatment with the antagonist. The same occurred with DZP, which saw its percentage of permanence time fall from 70.4% () to 6.5% () after administration of flumazenil, with no significant differences when compared to the control group ().

3.2. In Silico Testing
3.2.1. Docking Consensus

In this study, the results generated using the five scoring functions were validated through redocking of the crystallographic ligand. The RMSD of the positions obtained was calculated. Redocking consists of positioning and predicting the binding affinity of the crystallographic ligand in the region of the active site receiver. The RMSD compares and calculates the mean square root deviation of the positions obtained by redocking, and the ligand structure obtained experimentally. For docking to be considered reliable, the RMSD value must be equal to or less than 2.0 Å.

The programs MVD, Vina, and AD4 select the best binders for the most negative energy values, while the Gold and Plant programs select the best binders for the most positive energy values. HC obtained a higher binding affinity value than the crystallographic ligand (ABU), a cryo-EM structure of the α1β3γ2L receptor subunits in complex with GABA, in at least three of the programs (Table 1), indicating a satisfactory degree of affinity for the GABAAR. Computational techniques were then used to assess the stability of the bond.


MoleculeMoldock (MVD)Goldscore (Gold)Binding energy (AutoDock Vina)Binding energy (AutoDock)Chempl (Plants)

Gamma-aminobutyric acid (GABAA)
HC-75.4029.52-4.8-5.3837.94
PDB ABU-88.6526.22-5.7-4.9520.96

Figure 5 reveals that HC managed to form more stable interactions through hydrogen bonds with residues Arg67, Thr202, and Tyr157 in the region of the active site, whereas the ABU ligand formed a hydrogen interaction only with the amino acid Ser156. Steric interactions were also observed between residues Tyr205 and Tyr97 and the HC ligand, as well as interactions over short distances, which are more stable with residues Arg67, Tyr157, Thr202 and Tyr205, and HC.

3.2.2. Molecular Dynamics Simulations

The molecular dynamics (MD) simulations were performed taking into account the best results obtained in the consensus docking. The interactions between GABAAR and HC were evaluated, and the crystallographic ligand (ABU) was used to study the flexibility and conformational changes in the complexes during the MD simulations. For this, the mean quadratic deviation (RMSD) was separately calculated for the Cα atoms of the protein and the structures of each ligand. The RMSD analysis of GABAAR revealed that the protein reached conformations ranging from 0.3 to 0.4 nm in size in 10 ns. The results demonstrated that the protein is stable (Figure 6(a)), presenting no significant changes. In addition, when comparing the flexibility of the complexed protein to the ligands, we found that HC complexed to GABAAR remained stable most of the time, while the crystallographic ligand (ABU) complexed to GABAAR revealed structural change peaks between 3 and 4 nm.

RMSD analysis of the ligands revealed that HC is more stable than ABU (Figure 6(b)), suggesting that, although the protein undergoes minor structural changes, HC tends to remain within the active site longer, and the binding affinity is not lost, even in the presence of different factors such as temperature, solvent pressure, and ions.

To understand the flexibility of the residues and amino acids that contribute to GABAAR conformational changes, the mean square root fluctuation (RMSF) of each receptor amino acid was calculated. Residues with higher RMSF values suggest greater flexibility, while low RMSF values suggest less flexibility. Considering that amino acids with fluctuations above 0.3 nm contribute to the flexibility of the protein structure, we found that of the E and D chain amino acids that interacted with the agonist ligand ABU, not one contributed to a conformational change in the protein (Figure 6(c)). Since the active site is stable, the binding affinity for the compound tends to remain unchanged.

The docking interactions observed for the GABAAR-HC complex were stable during the molecular dynamics simulations. When analyzed using graphics programs, it was noted that HC loses interactions with the amino acids observed in docking (Figure 7), suggesting new interactions, appearing mainly through hydrogen bonds with the amino acids Phe35, Phe54, Arg56, and Glu492. Various factors may have contributed to this exchange of interactions between amino acids, such as for example, the interaction with compounds presenting water molecules and ions within the system defining the molecular dynamics.

3.2.3. In Silico Pharmacokinetic Predictions

The properties of medicines obtained in the ADMET system are the principal characteristics evaluated during the development phase of a future medicine. In new drug development, the ADMET forecast provides guidance that minimizes failure rates [40].

In silico pharmacokinetic predictions (Table 2) were performed using the ADMET parameters, with the aim of identifying possible pharmacokinetic disadvantages in the HC substance. According to Lipinski’s rules, a potential drug is orally active when it meets the following criteria: (a) molecular  Da, (b) (or ), (c) number of hydrogen bond , and (d) number of hydrogen bond [41].


CompoundabTPSA (Å2)cCaco-2 permeability (log Papp; log cm/s)dInt. Abs. (%)eVDss (log L/kg)fFract. Unb.gTotal clearance (log mL/min/kg)h

HC2.15-2.0437.301.4993.84-0.040.501.36

aSwissADME Moriguchi log of octanol-water partition coefficient. bSwissADME Ali log of aqueous solubility. cSwissADME calculation of Topological Polar Surface Area (TPSA). dpkCSM prediction of Caco-2 cell permeability as estimation of absorption in human intestinal mucosa. epkCSM prediction of the proportion of compound absorption thought the human small intestine.fpkCSM prediction of the log of steady state volume of distribution (VDss). gpkCSM prediction of compound fraction unbound in plasma (not bound to serum proteins). hpkCSM prediction of the log of total drug clearance.

HC presented a of 2.15, as well as adequate number of donors and acceptors of hydrogen bonds, complying with Lipinski rules and suggesting good bioavailability. In relation to , the value found for the compound was in the appropriate range (-4 and -2), indicating adequate solubility, which directly favors the bioavailability of the compound [42].

Molecules that present TPSA (Topological Polar Surface Area) values of less than 140 Å2 and values above 0.90 (log Papp; log cm/s), for the Caco-2 parameter, suggest that the substance presents a good profile for intestinal absorption. Such in vitro models are widely used to assess these parameters [43].

The volume of distribution (VDss) indicates the theoretical volume of a given substance evenly distributed in the blood plasma. Values below 0.45 (log L/kg) indicate a good plasma distribution, with the substance being readily available to interact with its biological target. Elimination of the substance did not increase because of its free form, as was observed for renal clearance (clearance/mL/min/kg). The greater the total clearance, the greater and faster the elimination of the substance will be [42, 44].

4. Discussion

According to a preliminary study, the oral LD50 of 7-HC was 5000 mg/kg [45]. In view of this result, the study of the LD50 estimate was initiated using the dose of 2000 mg/kg, i.p., aiming not to reach the lethal dose previously stipulated. However, even with the dose reduction to 2000 mg/kg, all animals died. This may have been due to the route of administration used. Therefore, the dose was again decreased, this time to 300 mg/kg.

In the initial toxicity test, during the 14-day observation period, after the administration of 300 mg/kg, i.p., no changes were found that would indicate toxicity, such as changes in the skin, hair, eyes, or respiratory system. The data demonstrated that under the evaluated conditions, HC presents low toxicity, providing an incentive to conduct in vivo pharmacological tests and allowing the choice of safe doses for these tests [9].

In vivo methodologies assess the anxiolytic-like activity of substances by inducing inhibitory behaviors in animals, in contrary to the stress caused by the environment to which they are subjected [46]. These inhibitory behaviors can be expressed by not realizing a movement or by increasing permanence time; these, since naturally, rodents are natural explorers. Substances with potential anxiolytic action must be able to reduce these inhibitory behaviors [47].

The behavioral changes induced upon HC administration (i.p.) were evaluated using the rotating bar (rota rod), elevated plus maze, and open field tests; these tests are well established in the study of substances with central nervous system activity, and except for the rotating bar test, they are models based on the observation of innate animal behavior, that is, on the ethology of rodents.

Rota rod testing is a classic animal model used to assess the influence of unknown substances on an animal’s motor coordination [26] when affected by agents such as benzodiazepines and anesthetics [25]. The test is carried out to illustrate the possible interference of the administered substance on motor coordination. Diazepam (DZP) causes impairment of balance or motor coordination, possibly due to neurotoxicity and thus restricts patient quality of life [48]; the use of diazepam (DZP), a reference drug in the treatment of anxiety (responsible for most reported side effects), as a control, allows comparison of motor locomotion impairment upon administration of HC. As was observed in the rota rod test, the animals’ locomotion was not compromised with administration of HC, differently from what was seen in the group treated with DZP. Thus, HC did not compromise the animals’ motor coordination.

To better evaluate the possible HC anxiolytic effects, the animals were subjected to the EPM test, which is considered one of the most well-established tests and the reference standard for detecting anxiolytic and anxiogenic effects [49]. The EPM test induces a conflict in the animal between exploring new environments and the tendency to avoid dangerous areas [47]. The administration of HC, in the three studied doses, significantly increased the percentage of entries and permanence in the open arms of the apparatus, in relation to the control group, indicating that acute administration of the compound increased the exploration behavior in the apparatus, indicating possible anxiolytic activity. The results are in line with studies that have demonstrated the anxiolytic activity of volatile, monoterpenoids, such as limonene, linalool, citronellal, and geranial, using the EPM methodology [46, 50, 51].

The open field test is widely used to assess behavioral effects of compound administration, especially in locomotor and anxious parameters [52, 53]. HC in the three doses tested was able to increase the locomotion of the animals towards exploring the apparatus quadrants, mainly the central quadrants. This behavior is associated with decreased anxiety levels in the animals, even when submitted to a new and stressful environment. In addition to the total number of crossings, other parameters can be observed in the open field test, such as the amount of self-cleaning (grooming) and vertical surveys (head rearings) [54, 55]. Thus, the greater the anxiety, the less number of head rearings and the more grooming. After treatments, the head rearing values increased significantly for the doses of 12.5 and 25 mg/kg, compared to the control group. The amount of grooming activity was reduced only when the dose of 25 mg/kg was administered. Reduction in self-cleaning is often seen in animals treated with compounds with potential anxiolytic activity [56]. The increase in the number of crosses in the open field test can be corroborated with the increase in the number of entries in the open arms of the elevated plus maze. The HC did not cause any change in the animals’ locomotion; this is proven due to the greater safety of the animals in walking through these regions of the labyrinth. The number of entries and length of stay, decreased, in the closed regions of the device, also reinforces this idea.

Finally, to assess whether the effects observed with HC involve interaction with the GABAergic system, the benzodiazepine GABAA receptor antagonist flumazenil was used. The antagonist was administered before the substances under study. If the pharmacological effect was reversed or even decreased significantly, it would mean that the antagonist, when binding to the target, prevented the substance from binding, and consequently, the pathway was involved in the pharmacological effect [57].

Pretreatment with the antagonist flumazenil reversed the anxiolytic-like effect of HC, as well as DZP, suggesting that HC is capable of reducing anxiety through a mechanism of action similar to that of BZDs (GABAAR). Interactions between GABAAR and other essential oils as well as their isolated compounds, such as citronellal, have been shown to result in CNS depressant activity [5860].

The positive modulation of the GABAA receptor by the enantiomer of the bicyclic monoterpene borneol, found in essential oils of medicinal herbs, such as valerian, was observed using electrophysiology models. Borneol directly activated GABAA receptors, producing 89% and 84%, respectively, of the maximum GABA response indicative of a partial agonist action, being insensitive to flumazenil, indicating that (+)- and (-)-borneol did not act in the classic sites of benzodiazepines [61]. HC has been shown to interact with the GABAA receptor in a common place for benzodiazepine binding, as its effect has been reversed by flumazenil. However, both studies demonstrate the interaction of these substances with the GABAergic receptor.

As discussed by Jiménez-Ferrer et al. [62], evaluating the anxiolytic effects of Aloysia triphylla fractions, which contained 21.6% citronellal, employed the EPM test and concluded that all fractions studied induced an anxiolytic-like effect. The activity was reversed with the use of a flumazenil antagonist. In another study, the sedative properties of Melissa officinalis include stress, agitation, and anxiety reduction which are attributed to the presence of phytochemicals, including citronellal (2.92%). The anxiolytic activity of M. officinalis has been attributed to a possible interaction with GABAA receptors, assuming activity similar to that of BZDs [63].

According to the position of Santos et al. [27], testing citronellal complexed with β-cyclodextrin observed an increase in the neuronal excitation threshold and a resulting decrease in muscle hyperalgesia. This effect is probably due to CNS activation, as discussed by Melo et al. [64] using the hot plate test, which had previously demonstrated that citronellal presents a central analgesic effect probably due to interaction with the GABAAR.

Substances that bind to GABAAR, such as benzodiazepines, cause a change in the conformational state of the receptor, which promotes increased affinity for the GABA neurotransmitter, stimulating the opening of GABAAR channels [65]. This results in hyperpolarization of the cell, reduced neuronal activity, and modified emotional states, all through anxiolytic, sedative, and muscle relaxing actions.

According to the data, the interaction of HC with GABAAR can result in greater neuronal hyperpolarization. After HC-GABAAR receptor binding, a greater influx of Cl- into the cell is suggested, regardless of GABA binding. Accumulation of chloride ions inside of the cell increases the threshold of neuronal excitation and prevents nerve impulse conduction [60, 66]. This general decrease in excitation can act in relieving the characteristic symptoms of anxiety.

Using in silico methodologies, the possible anxiolytic activity of the compound was also evaluated through involvement of the GABAA receptor, a principal biological target for anxiolytic substances. Computational methodologies, used in the initial stages of drug development, can unveil the character of unknown molecules and evaluate potential biological targets to better direct further study [67]. The most important inhibitory neurotransmitter in the central nervous system, without doubt, is gamma-aminobutyric acid (GABA). Any factor that promotes decreases in GABAergic transmission will result in the triggering of anxious and aggressive behaviors [68]. Through knowledge of the hydroxycitronellal (HC) structure, as well as that of GABAAR, it was possible to identify the potential agonist activity of the compound for this receptor, this, through the process of molecular complementarity [69].

When compared with the amino acids involved in the BZD-GABAAR interaction, the interaction of HC with GABAAR (through different amino acids) may be responsible for the observed nonimpairment of the test animals’ motor coordination. This revealed the potential of HC for use in formulating a new anxiolytic medication, which might allow patients to perform their daily functions normally, without the risk of accidents.

The hydrogen interactions between the amino acid residues of GABAAR and HC, compared to the ABU crystallographic ligand, presented greater affinity. The interactions between an enzyme and its substrate are complementary and were initially introduced in the famous “key-lock” model, proposed by Fischer [70]. Such complementarity, at the molecular level, would be observed through intermolecular interactions, represented by hydrophobic interactions, van der Waals, π clouds, hydrogen bonds, and electrostatic interactions [71].

Previous molecular docking studies between diazepam (DZP) and GABAARs [72] indicate that the drug binds to amino acids Lys105, Tyr160, Tyr210, and Val212 in the α1 subunit and to the amino acid Phe77 in the β2 subunit. HC in its stable binding form interacted with Arg67, Thr157, and Tyr157; this difference in amino acid binding is potentially the reason that the interaction between HC and GABAAR is more stable.

Molecular dynamics is important since it assesses structural differences between molecules, as was done for the HC and ABU agonists. The higher the RMSD value, the greater the structural difference between the proteins or structures were compared, as was observed for the HC ligand [73].

In this study, low RMSD values (>0.3 nm) were observed for the majority of the simulation time, indicating greater HC stability in the system compared to the crystallographic ligand (ABU). Sudden changes in RMSD denote important conformational changes in the molecule, while small RMSD oscillations indicate system equilibrium [74]; the equilibrium directly influences the interaction of the ligand and its receptor.

Through the molecular dynamics (MD) results, more stable HC-GABAAR bonding was observed. This stability may be related to the hydrogens of the CHO (aldehyde) functional groups, which can participate in nonclassical hydrogen bonds with certain amino acid residues, and such interactions with GABAAR amino acids can result in chloride ion influx into the cell, decreasing neuronal excitation.

To establish an adequate pharmacokinetic profile for HC, absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters were also evaluated. Absorption and distribution directly influence the bioavailability of the substance, while metabolism and excretion affect the rate of elimination of the substance from the body. Proper disposal of substances decreases the chances of toxic events being triggered [43].

To present a good bioavailability, a drug must obey at least three of the following parameters: molecular weight less than or equal to 500 Daltons (Da), high lipophilicity ( of less than 5), number of hydrogen bond donors (HBD) less than 5, and number of hydrogen bond acceptors (HBA) less than 10 [41]; no violation of these parameters was observed for HC.

HC was administered intraperitoneally in in vivo experiments, mainly due to its physical-chemical characteristics, such as liposolubility. The liposolubility of a substance determines its ability to permeate biological membranes and to reach its target [75]. The pharmacokinetic predictions revealed that HC has sufficient lipophilicity to interact with the lipid bilayer of biological membranes, as well as a water solubility compatible with the dissolution of the molecule in the aqueous biological fluid, resulting in good absorption.

5. Conclusions

Based on the data obtained in the present work, it is possible to conclude that hydroxycitronellal presents anxiolytic-like effect, which likely occurs through positive modulation of GABAA receptors. Ruling out HC neurotoxicity, the compound’s anxiolytic-like activity did not present adverse effects, such as sedation and neuromuscular impairment commonly observed in benzodiazepines. These findings reinforce the pharmacological potential of the monoterpene citronellal and its derivatives, such as hydroxycitronellal.

Data Availability

Some or all data, models, or code generated or used during the study are available from the corresponding author by request.

Conflicts of Interest

The authors declare no conflict of interest.

Acknowledgments

This study was supported by funds from the Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Council for Scientific and Technological Development (CNPq).

References

  1. D. M. da Silva, G. Sanz, B. G. Vaz et al., “Tert-butyl 4-((1-phenyl-1H-pyrazol-4-yl) methyl) piperazine-1-carboxylate (LQFM104)–new piperazine derivative with antianxiety and antidepressant-like effects: putative role of serotonergic system,” Biomedicine & Pharmacotherapy, vol. 103, pp. 546–552, 2018. View at: Publisher Site | Google Scholar
  2. A. M. V. Guimarães, A. C. da Silva Neto, A. T. S. Vilar, B. G. C. Almeida, A. F. O. Fermoseli, and Albuquerque C.M.F., “Anxiety disorders: a prevalence study on specific phobias and the importance of psychological help,” Undergraduate Notebook-Biological and Health Sciences, vol. 3, pp. 115–128, 2015. View at: Google Scholar
  3. M. B. Machado, Z. M. Ignácio, L. K. Jornada et al., “Prevalência de transtornos ansiosos e algumas comorbidades em idosos: um estudo de base populacional,” Jornal Brasileiro de Psiquiatria, vol. 65, no. 1, pp. 28–35, 2016. View at: Publisher Site | Google Scholar
  4. WH ORGANIZATION, Depression and other common mental disorders global health estimates, World Health Organization, 2017.
  5. F. Schifano, “Coming off prescribed psychotropic medications: insights from their use as recreational drugs,” Psychotherapy and Psychosomatics, vol. 89, no. 5, pp. 274–282, 2020. View at: Publisher Site | Google Scholar
  6. L. Fine, “Pharmacologic approach to insomnia,” Physical Medicine and Rehabilitation Clinics of North America, vol. 31, no. 2, pp. 255–264, 2020. View at: Publisher Site | Google Scholar
  7. L. Sousa, K. Graziani, G. Vedana, and A. I. Miasso, “Compliance with medication treatment by people with anxiety disorder,” Cogitare Enferm, vol. 21, no. 1, pp. 1–11, 2016. View at: Google Scholar
  8. S. S. Lima, R. de Oliveira Lima Filho, and G. A. L. de Oliveira, “Pharmacological aspects of Matricaria recutita (chamomile) in the treatment of generalized anxiety disorder and depressive symptoms,” Visão Acadêmica, vol. 20, no. 2, pp. 59–67, 2019. View at: Google Scholar
  9. A. A. C. De Almeida, J. P. Costa, R. B. F. De Carvalho, D. P. De Sousa, and R. M. De Freitas, “Evaluation of acute toxicity of a natural compound (+)-limonene epoxide and its anxiolytic-like action,” Brain Research, vol. 1448, pp. 56–62, 2012. View at: Publisher Site | Google Scholar
  10. D. P. De Sousa, P. D. A. S. Hocayen, L. N. Andrade, and R. Andreatini, “A systematic review of the anxiolytic-like effects of essential oils in animal models,” Molecules, vol. 20, no. 10, pp. 18620–18660, 2015. View at: Publisher Site | Google Scholar
  11. A. C. Lorenzo-Leal, E. Palou, A. López-Malo, and H. Bach, “Antimicrobial, cytotoxic, and anti-inflammatory activities of Pimenta dioica and Rosmarinus officinalis essential oils,” BioMed Research International, vol. 2019, Article ID 1639726, 2019. View at: Publisher Site | Google Scholar
  12. G. Chaves Neto, J. E. F. Braga, M. F. Alves et al., “Anxiolytic effect of Citrus aurantium L. in crack users,” Evidence-based Complementary and Alternative Medicine, vol. 2017, Article ID 7217619, 8 pages, 2017. View at: Publisher Site | Google Scholar
  13. L. R. L. Diniz, M. T. de Santana Souza, J. N. Barboza, R. N. de Almeida, and D. P. de Sousa, “Antidepressant potential of cinnamic acids: mechanisms of action and perspectives in drug development,,” Molecules, vol. 24, no. 24, p. 4469, 2019. View at: Publisher Site | Google Scholar
  14. D. V. da Fonsêca, C. da Silva Maia Bezerra Filho, T. C. Lima, R. N. de Almeida, and D. P. de Sousa, “Anticonvulsant essential oils and their relationship with oxidative stress in epilepsy,” Biomolecules, vol. 9, no. 12, pp. 835–840, 2019. View at: Publisher Site | Google Scholar
  15. P. R. R. Salgado, D. V. da Fonsêca, C. G. F. de Melo et al., “Comparison of behavioral, neuroprotective, and proinflammatory cytokine modulating effects exercised by (+)-cis-EC and (−)-cis-EC stereoisomers in a PTZ-induced kindling test in mice,” Fundamental & Clinical Pharmacology's, vol. 32, no. 5, pp. 507–515, 2018. View at: Publisher Site | Google Scholar
  16. D. P. De Sousa, F. F. F. Nóbrega, C. C. M. P. Santos, and R. N. De Almeida, “Anticonvulsant activity of the linalool enantiomers and racemate: investigation of chiral influence,” Natural Product Communications, vol. 5, no. 12, pp. 1847–1851, 2010. View at: Google Scholar
  17. D. P. De Sousa, “Analgesic-like activity of essential oils constituents,” Molecules, vol. 16, no. 3, pp. 2233–2252, 2011. View at: Publisher Site | Google Scholar
  18. R. M. Braga, H. H. N. de Andrade, H. D. Neto et al., “Antinociceptive and anti-inflammatory effect of Lippia pedunculosa hayek essential oil and its β-cyclodextrin inclusion complex,” Boletin Latinoamericano y del Caribe de Plantas Medicinales y Aromaticas, vol. 20, no. 2, pp. 162–176, 2021. View at: Google Scholar
  19. P. dos Passos Menezes, F. de Oliveira Araujo, T. A. Andrade et al., “Physicochemical characterization and antinociceptive effect of β-cyclodextrin/Lippia pedunculosa essential oil in mice,” Current Topics in Medicinal Chemistry, vol. 18, no. 9, pp. 797–807, 2018. View at: Publisher Site | Google Scholar
  20. V. la Rocca, D. V. da Fonsêca, K. S. Silva-Alves et al., “Geraniol induces antinociceptive effect in mice evaluated in behavioural and electrophysiological models,” Basic & Clinical Pharmacology & Toxicology, vol. 120, no. 1, pp. 22–29, 2017. View at: Publisher Site | Google Scholar
  21. J. Woo, H. Yang, M. Yoon et al., “3-Carene, a phytoncide from pine tree has a sleep-enhancing effect by targeting the GABAA-benzodiazepine receptors,” Experimental Neurobiology, vol. 28, no. 5, pp. 593–601, 2019. View at: Publisher Site | Google Scholar
  22. R. N. Almeida, R. N. Almeida, D. S. Navarro, and J. M. Barbosa-Filho, “Plants with central analgesic activity,” Phytomedicine, vol. 8, no. 4, pp. 310–322, 2001. View at: Publisher Site | Google Scholar
  23. R. N. De Almeida, S. C. Motta, C. De Brito Faturi, B. Catallani, and J. R. Leite, “Anxiolytic-like effects of rose oil inhalation on the elevated plus-maze test in rats,” Pharmacology, Biochemistry, and Behavior, vol. 77, no. 2, pp. 361–364, 2004. View at: Publisher Site | Google Scholar
  24. L. J. Quintans-Júnior, T. T. Souza, B. S. Leite et al., “Phythochemical screening and anticonvulsant activity of Cymbopogon winterianus Jowitt (Poaceae) leaf essential oil in rodents,” Phytomedicine, vol. 15, no. 8, pp. 619–624, 2008. View at: Publisher Site | Google Scholar
  25. A. De Moraes Pultrini, L. Almeida Galindo, and M. Costa, “Effects of the essential oil from Citrus aurantium L. in experimental anxiety models in mice,” Life Sciences, vol. 78, no. 15, pp. 1720–1725, 2006. View at: Publisher Site | Google Scholar
  26. N. W. Dunham and T. S. Miya, “A note on a simple apparatus for detecting neurological deficit in rats and mice,” Journal of the American Pharmacists Association, vol. 46, no. 3, pp. 208-209, 1957. View at: Google Scholar
  27. P. L. Santos, R. G. Brito, M. A. Oliveira et al., “Docking, characterization and investigation of β-cyclodextrin complexed with citronellal, a monoterpene present in the essential oil of Cymbopogon species, as an anti-hyperalgesic agent in chronic muscle pain model,” Phytomedicine, vol. 23, no. 9, pp. 948–957, 2016. View at: Publisher Site | Google Scholar
  28. M. T. de Santana, M. G. B. de Oliveira, M. F. Santana et al., “Citronellal, a monoterpene present in Java citronella oil, attenuates mechanical nociception response in mice,” Pharmaceutical Biology, vol. 51, no. 9, pp. 1144–1149, 2013. View at: Publisher Site | Google Scholar
  29. S. Pellow and S. E. File, “Anxiolytic and anxiogenic drug effects on exploratory activity in an elevated plus-maze: a novel test of anxiety in the rat,” Pharmacology, Biochemistry, and Behavior, vol. 24, no. 3, pp. 525–529, 1986. View at: Publisher Site | Google Scholar
  30. J. Archer, “Tests for emotionality in rats and mice: a review,” Animal Behavior, vol. 21, no. 2, pp. 205–235, 1973. View at: Publisher Site | Google Scholar
  31. G. Biala and M. Kruk, “Calcium channel antagonists suppress cross-tolerance to the anxiogenic effects of D-amphetamine and nicotine in the mouse elevated plus maze test,” Progress in Neuro-Psychopharmacology & Biological Psychiatry, vol. 32, no. 1, pp. 54–61, 2008. View at: Publisher Site | Google Scholar
  32. G. Imre, G. Veress, A. Volford, and Ö. Farkas, “Molecules from the Minkowski space: an approach to building 3D molecular structures,” Journal of Molecular Structure: THEOCHEM, vol. 666-667, pp. 51–59, 2003. View at: Publisher Site | Google Scholar
  33. R. Thomsen and M. H. Christensen, “MolDock: a new technique for high-accuracy molecular docking,” Journal of Medicinal Chemistry, vol. 49, no. 11, pp. 3315–3321, 2006. View at: Publisher Site | Google Scholar
  34. M. J. Abraham, T. Murtola, R. Schulz et al., “GROMACS: high performance molecular simulations through multi-level parallelism from laptops to supercomputers,” Software X, vol. 1-2, pp. 19–25, 2015. View at: Publisher Site | Google Scholar
  35. H. J. C. Berendsen, D. van der Spoel, and R. van Drunen, “GROMACS: a message-passing parallel molecular dynamics implementation,” Computer Physics Communications, vol. 91, no. 1–3, pp. 43–56, 1995. View at: Publisher Site | Google Scholar
  36. A. K. Malde, L. Zuo, M. Breeze et al., “An automated force field topology builder (ATB) and repository: version 1.0,” Journal of Chemical Theory and Computation, vol. 7, no. 12, pp. 4026–4037, 2011. View at: Publisher Site | Google Scholar
  37. A. Bondi, “van Der Waals volumes and radii,” Journal of Physical Chemistry A, vol. 68, no. 3, pp. 441–451, 1964. View at: Publisher Site | Google Scholar
  38. E. F. Pettersen, T. D. Goddard, C. C. Huang et al., “CSF Chimera - a visualization system for exploratory research and analysis,” Journal of Computational Chemistry, vol. 25, no. 13, pp. 1605–1612, 2004. View at: Publisher Site | Google Scholar
  39. A. Daina, O. Michielin, and V. Zoete, “SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules,” Scientific Reports, vol. 7, no. 1, pp. 1–13, 2017. View at: Publisher Site | Google Scholar
  40. S. Clarysse, J. Brouwers, J. Tack, P. Annaert, and P. Augustijns, “Intestinal drug solubility estimation based on simulated intestinal fluids: comparison with solubility in human intestinal fluids,” European Journal of Pharmaceutical Sciences, vol. 43, no. 4, pp. 260–269, 2011. View at: Publisher Site | Google Scholar
  41. C. A. Lipinski, F. Lombardo, B. W. Dominy, and P. J. Feeney, “Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25. 1,” Advanced Drug Delivery Reviews, vol. 46, no. 1-3, pp. 3–26, 2001. View at: Publisher Site | Google Scholar
  42. D. Elder and R. Holm, “Aqueous solubility: simple predictive methods (in silico, in vitro and bio-relevant approaches),” International Journal of Pharmaceutics, vol. 53, no. 1, pp. 3–11, 2013. View at: Google Scholar
  43. A. D. T. O. Moraes, M. D. S. . Miranda, Í. T. T. Jacob et al., “Synthesis, _in vitro_ and _in vivo_ biological evaluation, COX-1/2 inhibition and molecular docking study of indole- _N_ -acylhydrazone derivatives,” Bioorganic & Medicinal Chemistry, vol. 26, no. 20, pp. 5388–5396, 2018. View at: Publisher Site | Google Scholar
  44. C. Lambertucci, G. Marucci, D. Dal Ben et al., “New potent and selective A1 adenosine receptor antagonists as potential tools for the treatment of gastrointestinal diseases,” European Journal of Medicinal Chemistry, vol. 151, pp. 199–213, 2018. View at: Publisher Site | Google Scholar
  45. K. E. Malten, W. G. van Ketel, J. P. Nater, and D. H. Liem, “Reactions in selected patients to 22 fragrance materials,” Contact Dermatitis, vol. 11, no. 1, pp. 1–10, 1984. View at: Publisher Site | Google Scholar
  46. L. Caputo, M. Reguilon, J. Mińarro, V. De Feo, and M. Rodriguez-Arias, “Lavandula angustifolia essential oil and linalool counteract social aversion induced by social defeat,” Molecules, vol. 23, no. 10, p. 2694, 2018. View at: Publisher Site | Google Scholar
  47. A. C. Campos, M. V. Fogaça, D. C. Aguiar, and F. S. Guimarães, “Animal models of anxiety disorders and stress,” Revista Brasileira de Psiquiatria, vol. 35, SUPPL.2, pp. S101–S111, 2013. View at: Publisher Site | Google Scholar
  48. T. D. Prevot, G. Li, A. Vidojevic et al., “Novel benzodiazepine-like ligands with various anxiolytic, antidepressant, or pro-cognitive profiles,” Molecular Neuropsychiatry, vol. 5, no. 2, pp. 84–97, 2019. View at: Publisher Site | Google Scholar
  49. S. Hogg, “A review of the validity and variability of the elevated plus-maze as an animal model of anxiety,” Pharmacology Biochemistry and Behavior, vol. 54, no. 1, pp. 21–30, 1996. View at: Publisher Site | Google Scholar
  50. L. M. L. Campêlo, A. A. C. de Almeida, R. L. M. de Freitas et al., “Antioxidant and antinociceptive effects of Citrus limon essential oil in mice,” Journal of Biomedicine and Biotechnology, vol. 2011, Article ID 678673, 8 pages, 2011. View at: Publisher Site | Google Scholar
  51. V. M. Linck, A. L. da Silva, M. Figueiró, E. B. Caramão, P. R. H. Moreno, and E. Elisabetsky, “Effects of inhaled linalool in anxiety, social interaction and aggressive behavior in mice,” Phytomedicine, vol. 17, no. 8–9, pp. 679–683, 2010. View at: Publisher Site | Google Scholar
  52. E. Choleris, A. W. Thomas, M. Kavaliers, and F. S. Prato, “A detailed ethological analysis of the mouse open field test: effects of diazepam, chlordiazepoxide and an extremely low frequency pulsed magnetic field,” Neuroscience & Biobehavioral Reviews, vol. 25, no. 3, pp. 235–260, 2001. View at: Publisher Site | Google Scholar
  53. A. L. S. Rodrigues, J. B. T. Rocha, C. F. Mello, and D. O. Souza, “Effect of perinatal lead exposure on rat behaviour in open-field and two-wky avoidance tasks,” Basic & Clinical Pharmacology & Toxicology, vol. 79, no. 3, pp. 150–156, 1996. View at: Publisher Site | Google Scholar
  54. A. V. Kalueff, C. L. Jensen, and D. L. Murphy, “Locomotory patterns, spatiotemporal organization of exploration and spatial memory in serotonin transporter knockout mice,” Brain Research, vol. 1169, no. 1, pp. 87–97, 2007. View at: Publisher Site | Google Scholar
  55. D. G. Machado, M. P. Cunha, V. B. Neis et al., “Fluoxetine reverses depressive-like behaviors and increases hippocampal acetylcholinesterase activity induced by olfactory bulbectomy,” Pharmacology, Biochemistry, and Behavior, vol. 103, no. 2, pp. 220–229, 2012. View at: Publisher Site | Google Scholar
  56. J. T. Ting and G. Feng, “Neurobiology of obsessive-compulsive disorder: insights into neural circuitry dysfunction through mouse genetics,” Current Opinion in Neurobiology, vol. 21, no. 6, pp. 842–848, 2011. View at: Publisher Site | Google Scholar
  57. H. d. C. Aragão Neto, D. V. da Fonsêca, R. M. Braga et al., “2-Allylphenol reduces IL-1β and TNF-α, promoting antinociception through adenosinergic, anti-inflammatory, and antioxidant mechanisms,” Oxidative Medicine and Cellular Longevity, vol. 2019, Article ID 1346878, 14 pages, 2019. View at: Publisher Site | Google Scholar
  58. C. G. Heldwein, L. L. Silva, P. Reckziegel et al., “Participation of the GABAergic system in the anesthetic effect of Lippia alba (Mill.) N.E. Brown essential oil,” Brazilian Journal of Medical and Biological Research, vol. 45, no. 5, pp. 436–443, 2012. View at: Publisher Site | Google Scholar
  59. C. G. Heldwein, L. . L. Silva, E. Z. Gai et al., “_S_ -(+)-Linalool from _Lippia alba_ : sedative and anesthetic for silver catfish ( _Rhamdia quelen_ ),” Veterinary Anaesthesia and Analgesia, vol. 41, no. 6, pp. 621–629, 2014. View at: Publisher Site | Google Scholar
  60. Q. I. Garlet, L. C. Pires, D. T. Silva et al., “Effect of (+)-dehydrofukinone on GABAA receptors and stress response in fish model,” Brazilian Journal of Medical and Biological Research, vol. 49, no. 1, article e4872, 2016. View at: Publisher Site | Google Scholar
  61. R. E. Granger, E. L. Campbell, and G. A. R. Johnston, “(+)- and (-)-borneol: efficacious positive modulators of GABA action at human recombinant α1β2γ2L GABAA receptors,” Biochemical Pharmacology, vol. 69, no. 7, pp. 1101–1111, 2005. View at: Publisher Site | Google Scholar
  62. E. Jiménez-Ferrer, M. A. Santillán-Urquiza, E. Alegría-Herrera et al., “Anxiolytic effect of fatty acids and terpenes fraction from Aloysia triphylla: serotoninergic, GABAergic and glutamatergic implications,” Biomedicine & Pharmacotherapy, vol. 96, pp. 320–327, 2017. View at: Publisher Site | Google Scholar
  63. B. L. Fermino, N. N. Khalil, J. S. Bonini, R. P. Romaiana, J. B. T. Rocha, and W. C. F. N. Silva, “Anxiolytic properties of Melissa officinalis and associated mechanisms of action: A review of the literature,” African Journal of Pharmacy and Pharmacology, vol. 9, pp. 53–59, 2015. View at: Google Scholar
  64. M. S. Melo, L. C. S. Sena, F. J. N. Barreto et al., “Antinociceptive effect of citronellal in mice,” Pharmaceutical Biology, vol. 48, no. 4, pp. 411–416, 2010. View at: Publisher Site | Google Scholar
  65. A. Guidotti, M. Baraldi, A. Leon, and E. Costa, “Benzodiazepines: a tool to explore the biochemical and neurophysiological basis of anxiety,” Brazilian Journal of Medical and Biological Research, vol. 36, no. 4, 1980. View at: Google Scholar
  66. C. B. Faturi, J. R. Leite, P. B. Alves, A. C. Canton, and F. Teixeira-Silva, “Anxiolytic-like effect of sweet orange aroma in Wistar rats,” Neuro-Psychopharmacology & Biological Psychiatry, vol. 34, no. 4, pp. 605–609, 2010. View at: Publisher Site | Google Scholar
  67. C. B. R. Santos, C. C. Lobato, F. S. Braga et al., “Application of Hartree-Fock method for modeling of bioactive molecules using SAR and QSPR,” Computational Molecular Bioscience, vol. 4, no. 1, pp. 1–24, 2014. View at: Publisher Site | Google Scholar
  68. R. Narvaes and R. M. M. de Almeida, “Aggressive behavior and three neurotransmitters: dopamine, GABA, and serotonin—a review of the last 10 years,” Psychology & Neuroscience, vol. 7, no. 4, pp. 601–607, 2014. View at: Publisher Site | Google Scholar
  69. H. M. Berman, G. J. Kleywegt, H. Nakamura, and J. L. Markley, “How community has shaped the protein data bank,” Structure, vol. 21, no. 9, pp. 1485–1491, 2013. View at: Publisher Site | Google Scholar
  70. E. Fischer, “Einfluss der configuration auf die wirkung der enzyme,” European Chemical Societies Publishing, vol. 27, no. 3, pp. 2985–2993, 1894. View at: Google Scholar
  71. H. Verli and E. J. Barreiro, “Um paradigma da química medicinal: a flexibilidade dos ligantes e receptores,” Quimica Nova, vol. 28, no. 1, pp. 95–102, 2005. View at: Publisher Site | Google Scholar
  72. R. Bergmann, K. Kongsbak, P. L. Sørensen, T. Sander, and T. Balle, “A unified model of the GABAA receptor comprising agonist and benzodiazepine binding sites,” PLoS One, vol. 8, no. 1, article e52323, 2013. View at: Publisher Site | Google Scholar
  73. K. Sargsyan, C. Grauffel, and C. Lim, “How molecular size impacts RMSD applications in molecular dynamics simulations,” Journal of Chemical Theory and Computation, vol. 13, no. 4, pp. 1518–1524, 2017. View at: Publisher Site | Google Scholar
  74. O. Carugo, “How root-mean-square distance (R.M.S.D.) values depend on the resolution of protein structures that are compared,” Journal of Applied Crystallography, vol. 36, no. 1, pp. 125–128, 2003. View at: Publisher Site | Google Scholar
  75. J. R. Santin, F. D. T. Uchôa, M. D. C. A. Lima et al., “Chemical synthesis, docking studies and biological effects of a pan peroxisome proliferator-activated receptor agonist and cyclooxygenase inhibitor,” European Journal of Pharmaceutical Sciences, vol. 48, no. 4–5, pp. 689–697, 2013. View at: Publisher Site | Google Scholar

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