Abstract

The use of natural products has been gaining a lot of attention in recent years, among them organic honey, with its high phenolic content, has great potential in fighting diseases. The Aroeira-do-Sertão (Astronium urundeuva) is a tree that, when it blooms, is pollinated by bees and produces a honey rich in nutrients that is widely used by the population to treat flu and other symptoms. Leprosy and tuberculosis are two of the main neglected diseases that occur frequently in underdeveloped countries, where a large part of the population is vulnerable to contagion and treatment is often ineffective. Such diseases can cause several symptoms such as motor loss and major respiratory complications in patients. Recent research shows a great interest of the pharmaceutical industry in the production of medicines and in the fight against these diseases, opening a great opportunity for studies to present satisfactory results. The present study seeks to carry out an in-silico investigation of the main constituents of Aroeira honey, performing pharmacokinetic predictions through ADME-Tox platforms. From molecular docking, simulations were performed with the proteins ML2640c, PknA and PknB, in which the ligands Quercetin (−8.8 kcal/mol), Ellagic acid (−8.3 kcal/mol) and Luteolin (−8.1 kcal/mol) present the best binding affinities with important amino acid residues of the catalytic site. In addition, anticarcinogenic, anti-inflammatory and antibacterial activities were predicted for these compounds, but more in-depth studies, such as in vitro and in vivo assays, are necessary to prove the biological activity of these molecules.

1. Introduction

2. Materials and Methods

3. Results and Discussion

3.1. Compounds Present in Aroeira-do-Sertão Honey

Aroeira honey is characterized by its dark color and exotic flavor, which is attractive to the consumer’s palate. In addition to being widely consumed by local people, Aroeira honey is the subject of medicinal studies that correlate the chemical constituents of honey with medicinal treatments and the production of phytopharmaceuticals [32,33,34,35,36,37,38].

Studies on the physical-chemical characterization of Aroeira honey shows a high phenolic load among the compounds, in addition to B vitamins [80], derived from acids of natural origin and minerals such as Iron, Magnesium, and Calcium [81]. During the research, several compounds were found in Aroeira honey, among them the most used in several natural products, such as flavonoids, Quercetin, Luteolin, Ellagic Acid, Fisetin, Rutin and other compounds classified in Aroeira honey. To avoid doubts, all the compounds found are indicated in Supplementary Table S1, where the large presence of phenolic compounds, acids, and other natural substances found in Aroeira honey is notable.

Recent and old studies indicate a great phytotherapeutic potential of flavonoids in combating various symptoms, including potential antioxidant, anti-inflammatory, and, most importantly for the purpose of this research, antibacterial uses. Studies such as [82,83,84,85,86] promote a large collection of flavonoids that act on bacterial diseases to reduce the proliferation of bacteria in the body.

These phytotherapeutic actions of flavonoids are due to the molecular structure of the compounds, and the structures are similar, sharing the same basic skeleton, differing only in the functional groups, and this is exactly what delimits the phytotherapeutic potential of flavonoids. The presence of isomers among flavonoids is very common. Their structure is represented in Figure 1.

Observing its structure in Figure 1, it is evident that the functional groups can be arranged in various ways. According to the studies of [85,86], the functional groups that link together give rise to several other compounds and classes of flavonoids, as well as different medicinal properties. For example, flavonols exhibit specific characteristics when hydroxyl groups are present in the aromatic ring, C5–C8, and/or in C1′–C6′, in addition to a ketone at C4 and a double bond forming a pyrene at C2–C3. Also, the different forms of organization of the functional groups lead to new compounds, giving rise to flavones, containing only alcohol (-OH) as a functional group arranged in different carbons in the structure. The different constitutional organizations of the basic skeleton also lead to new compounds with different properties, making it justifiable that different functional groups lead to different medicinal properties.

3.2. ADME-Tox Predictions

During the ADME-tox tests, two sets of predictions were performed, the first of which was performed to delimit, based on key predictions, which compounds, if isolated, end up causing harm to the body. Among the parameters used, some key parameters were considered (BBB, Rule of Five, P-gp, Carcino Mouse, and Carcino Rat) to isolate the compounds and reduce the number of compounds to be predicted and used in the Docking simulations.

Supplementary Table S2 shows the values and parameters used to isolate the compounds. Under no circumstances should the compounds cross the blood-brain barrier. If this happens, the compound could cause damage to the Central Nervous System (CNS), the brain, and damage adjacent to the CNS [87]. As is the case with the compound Abscisic Acid where it crosses the barrier, causing possible damage to the CNS. Compounds that cross the Blood-Brain Barrier or are positive in the rodent groups (rat and mouse) are discarded. However, compounds that show alternating positivity in the rodent groups are kept, which is the case with some of the compounds, such as Quercetin, which showed alternating positivity in the rodent groups.

Among the compounds in Supplementary Table S2, it is preferable that they present normal to high intestinal absorption, but this does not reflect in the classification of the compounds, it only dictates how quickly the compound is absorbed in the stomach.

The Rule of 5 denotes certain parameters that candidates must fulfill to be classified: a molecular weight of no more than 500 g/mol, an n-octanol water partition coefficient (Log P _O/W) of no more than 5, hydrogen donors of no more than 5, and hydrogen bond acceptors of no more than 10 [72]. For compounds that do not respect the Rule of 5, they have been eliminated, even if only a few aspects do not fit the rule, as is the case with Myricetin, which passed the parameters of BBB and Carcino Rat and Mouse but presented a violation of the Rule of 5 (NhorH > 5). The same reasoning for Chlorogenic Acid, where it respects the parameters of BBB and Carcino Rat and Mouse but a violation of the Rule of 5 (NhorH > 5). This does not mean that the compound is unusable; it was just established that the compounds that did not fully respect the Rule of 5 were not selected for the next stages of investigation. These parameters were checked in SWISSADME.

By isolating the compounds that respected the parameters defined in the first set of predictions, the second set of predictions is carried out, where new parameters that determine the pharmacokinetic and pharmacodynamic part of the candidate compounds are considered. Therefore, Supplementary Table S3 shows the separated compounds as well as their predicted values.

Analyzing Supplementary Table S3, the first point analyzed is the solubility values. For this study, Log S (ESOL) was used which relates the solubility of the compound. According to [71] the values to be analyzed cannot be less than −6.00 and greater than 0.00. For a better understanding of the Log S (ESOL) value, the aqueous solubility potential is denoted right after, where the closer to zero, the greater the solubility of the compound. Almost all the compounds proved to be within the parameters recommended by [71], However, one of the compounds, Succinic Acid, showed a value of 0, indicating a high solubility potential, as did Caffeic Acid (−1.89).

Caco2 and MDCK cells are very important cells when it comes to administration, compound absorption, delivery to different areas of the human body, and drug design. All in all, the compounds should not obtain values greater than 70 nm/s for Caco2 cells. It is preferable for them to have only medium permeability, with values between 4–70 nm/s. However, studies such as that by [88,89] indicate that high permeabilities have a positive impact on phytopharmaceutical studies. Only a few of the compounds proved to be contrary to the values for Caco2, falling below the recommended level, with Quercetin (3.412), Quercetin 3,3′-dimethyl ether (2.996), Baicalein (1.280), Catechin (0.656), Epicatechin (0.656), and Pinobanksin (3.691) being the compounds that fell below the recommended level.

MDCK cells are of great help in the transportation of compounds through the body, so medium values are necessary in order not to cause damage to the respective cells. According to the studies of [88], the values to be considered are between 25–500, which delimits medium permeability in the cells. Once again, some compounds exhibited values that were contrary to the recommended levels, with two of them being significantly lower: Succinic Acid (8.511) and Rosmarinic Acid (0.202), respectively.

The AMES Salmonella test is carried out on strains of the Salmonella typhimurium species to determine the chemical and genetic mutation potential of the candidates. We determined two strains, TA100 and TA1535. Compounds that test positive indicate a high potential for chemical and biological mutations in the compounds. It is preferable for candidates not to be positive, but studies such as that of [78] indicate that compounds, even if they are positive in the tests, are usable in biological tests, and small mutations can be made to the structure of the compound so as not to harm the guinea pigs. For the AMES test, all the compounds showed mutagenicity. For the AMES Salmonella test, the compounds should not show mutagenicity in both groups (TA100 and TA1535), as is the case with Quercetin, Kaempferol, Kaempferide, Isoharminetin, Luteolin, Baicalein, Hesperetin, Eridictyol, Fisetin, Catechin and Epicatechin, which were negative in the TA100_10RLI strains and both the TA1535_10RLI and TA1535_NA strains, but positive in the TA100_NA strain. Of all the compounds, only one showed negativity in all the TA100 and TA1535 strains, Lumichrome.

Human Intestinal Absorption (HIA) is a parameter that determines how well a compound can be absorbed by the human intestine. It is preferable for compounds to have values greater than 70, indicating a high potential for intestinal absorption. Values below 70 indicate that the compound may take a while to be absorbed by the intestine [73]. Some compounds were below the recommended values, such as Succinic Acid (54.538), Quercetin (63.485), Rosmarinic Acid (62.487), Gallic Acid (53.696), Ellagic Acid (61.395), Catechin (66.707) and Epicatechin (66.707).

3.3. Biological Prediction

The biological predictions were performed on the PASSONLINE platform, where the most recurrent biological activities were searched for in articles such as [70]. Among the various results of PASSONLINE, the potential for anti-inflammatory, antioxidant, antibacterial, anticarcinogenic, and healing actions was analyzed.

Among the results, it is preferable that they are above 0.500 for activity potentials (pa); however, activity values greater than inactivity values (pi) still report an activity potential, even if low. The values can be seen in Table 1.

Table 1:

Biological activity values of the best compounds in Aroeira honey.

Compounds	Anti-Inflammatory		Antioxidant		Antibacterial		Anticarcinogenic		Healing
	Pa	Pi	Pa	Pi	Pa	Pi	Pa	Pi	Pa	Pi
Caffeic Acid	0.651	0.023	0.603	0.005	0.358	0.041	0.571	0.014	0.225	0.094
Vanillic Acid	0.505	0.055	0.374	0.014	0.376	0.036	0.413	0.029	0.267	0.067
Quercetin	0.689	0.017	0.872	0.003	0.387	0.033	0.757	0.003
Quercetin 3,3′-dimethyl ether	0.707	0.015	0.777	0.004	0.985	0.034	0.778	0.006
Quercetin 7,3′-dimethyl ether	0.710	0.014	0.754	0.004	0.384	0.034	0.746	0.007
Apigenin	0.644	0.024	0.732	0.004	0.391	0.032	0.641	0.011	0.256	0.073
Kaempferol	0.676	0.019	0.856	0.003	0.395	0.031	0.715	0.008	0.174	0.151
Kaempiferide	0.627	0.026	0.765	0.004	0.365	0.039	0.733	0.008
Isoharmetin	0.663	0.021	0.809	0.003	0.375	0.037	0.779	0.006
Genistein	0.626	0.027	0.765	0.004	0.394	0.031	0.715	0.004	0.191	0.128
Luteolin	0.661	0.021	0.775	0.004	0.388	0.033	0.690	0.009
Baicalein	0.674	0.019	0.801	0.003	0.399	0.030	0.610	0.012	0.182	0.140
Hesperetin	0.640	0.024	0.746	0.004	0.370	0.038	0.783	0.006
Narigenin	0.660	0.021	0.794	0.003	0.397	0.031	0.724	0.008
Eriodictiol	0.691	0.017	0.817	0.003	0.395	0.031	0.775	0.006
Gentisicacid	0.716	0.014	0.406	0.012	0.419	0.026	0.409	0.029	0.305	0.045
Rosmarinicacid	0.453	0.072	0.539	0.005	0.222	0.100	0.398	0.031	0.183	0.139
Lumicrome							0.252	0.082	0.166	0.163
Sinapic Acid	0.612	0.029	0.576	0.005	0.359	0.041	0.616	0.012	0.179	0.144
Saringic Acid	0.498	0.058	0.403	0.012	0.395	0.031	0.413	0.029	0.252	0.076
Gallic Acid	0.548	0.044	0.520	0.006	0.418	0.026	0.395	0.031	0.276	0.061
Ellagic Acid	0.749	0.010	0.699	0.004	0.380	0.035	0.396	0.031
Protocatechuic acid	0.538	0.046	0.401	0.012	0.394	0.032	0.387	0.033	0.302	0.047
Fisetin	0.642	0.024	0.787	0.004	0.346	0.044	0.687	0.009
Galangin	0.689	0.017	0.853	0.003	0.393	0.032	0.703	0.009	0.176	0.148
Catechin	0.548	0.044	0.810	0.003	0.320	0.053	0.795	0.005
Epicatechin	0.548	0.044	0.810	0.003	0.320	0.053	0.795	0.005
Pinobanksin	0.712	0.014	0.940	0.002	0.381	0.035	0.780	0.006
Dl-p-hydroxyphenyllact acid			0.285	0.026	0.201	0.117	0.382	0.034	0.195	0.123

Font: Way2Drug (PASSONLINE), 2024.

It is noteworthy that the compounds vary in their values; not all compounds exhibit high activity in the selected areas, but many demonstrate strong activity in other areas, as shown in Table 1. As is notable for the Isoharmnetin compound, which showed an excellent value for antioxidant activities, but which showed no healing activity or a very low activity, it was not possible to obtain its values. The same can be said for Fisetin, which has interesting anti-inflammatory, antioxidant, antibacterial and anticarcinogenic values, but has no value for healing potential. This shows the great complexity of Aroeira honey and the great bioactivity of Aroeira honey.

3.4. Molecular Docking

After selecting the ligands, the Molecular Docking simulations began. Docking was performed on the three bacterial proteins using the coordinates established by CavityPlus, and the results of the Binding Energies of the ML2640c, PknA and PknB protein can be seen in Table 2.

Table 2:

Binding Energy values from Molecular Docking simulations with the respective targets.

Ligands	Receptors PDB ID
	2UYO	4OW8	1MRU
	Kcal/mol	Kcal/mol	Kcal/mol
Quercetin	−8.8	−8.0	−7.7
Fisetin	−8.8	−7.7	−7.4
Luteolin	−8.6	−7.7	−8.1
Baicalein	−8.4	−7.4	−7.8
Eriodictiol	−8.4	−7.7	−7.9
Hesperetin	−8.3	−7.8	−7.7
Catechin	−8.3	−7.7	−7.5
Epicatechin	−8.2	−7.2	−7.7
Apigenin	−8.2	−7.6	−7.8
Rosarinic	−8.2	−7.5	−8.0
Kaempferol	−8.2	−7.7	−7.5
Narigenin	−8.2	−7.5	−7.6
Ellagic acid	−8.1	−8.3	−8.1
Isoharminetin	−8.1	−7.6	−8.1
Quercetin 3,3′-dimethyl ether	−8.1	−7.2	−7.9
Lumichrome	−8.0	−7.5	−7.5
Quercetin 7,3′-dimethyl ether	−8.0	−7.6	−7.2
Pinobanquisin	−7.9	−7.6	−7.3
Genistein	−7.8	−7.1	−7.2
Kaempferide	−7.8	−7.7	−7.5
Galangin	−7.7	−7.7	−7.5
Caffeic Acid	−6.5	−6.0	−6.1
Dl-p-hydroxyphenyllact acid	−6.5	−6.1	−5.4
Gallic acid	−6.2	−5.5	−5.3
SinapicAcid	−6.1	−5.8	−5.7
Gentisicacid	−6.0	−5.1	−5.1
Protocatechuic acid	−5.9	−5.6	−5.3
Syringicacid	−5.9	−5.5	−5.3
Vanillicacid	−5.7	−5.5	−5.2

Font: AutoDock Vina, 2024.

It is noteworthy that most of the ligands obtained good binding energies, which according to studies by [53] determine that values below −7.0 are ideal for the assembly and analysis of the complexes. Among all the dockings worked on for all the protein targets, the complex was assembled for only two ligands of each target worked on.

Therefore, the binding energies for 2UYO (Quercetin and Fisetin) are exceptionally low (−8.8 and −8.8) suggesting very good anchoring. This low binding energy affects the chemical accessibility of the ligands in relation to the protein residues since their entrapment based on van der Waals forces ensures better direct interaction and ligand stability considering the frequent motions and chemical reactions of the protein. Moreover, an increase in the size of the ligand is also observed altering the binding energy value; therefore, large ligands interact with more residues than the small ligand. For 4OW8 (Ellagic Acid and Quercetin) the same principle applies, where their resulting binding energy was −8.3 and −8.0 respectively, being optimal binding energy values, as well as the values for 1MRU (Luteolin and Isorhamnetin) where their respective binding energy values are −8.1 and −8.1, signaling that the ligands are perfectly anchored within the catalytic site.

After successful anchoring of the ligands in the protein, a series of chemical interactions between the amino acid residues are expected, where the interactions can be very diverse, depending, of course, on the atoms and their reactive nature of both the amino acid residue and the ligand. For the purpose of phytopharmaceutical design the interactions to be investigated are hydrophobic interactions and hydrogen bonds. As noted by the work of [72], these interactions are useful in shielding of the ligand from other fierce biological interactions with the protein. Furthermore, stated by [90] hydrogen bonds originate from static charge between bottom bonds from elements more electronegative than hydrogen primarily oxygen. These interactions are considered to be important because they weaken the cell walls of the protein, thereby creating entry point for the drugs. In certain cases, they may degrade the protein; they will not allow any physiological repair mechanism to occur; this leads to cell necrosis.

Not only are these interactions essential, but there are interactions that favor ligand anchoring, which are the van der Wals interactions [90]. Interactions that play a crucial role in the stability of the ligand within the cavity. The Pi-Cation interactions [91] and interactions between the pi electron-rich orbitals that help to keep the ligand less volatile, being the Amide-pi Stacked interactions, carried out by the overlap of amide groups. All these interactions are essential in drug design because they play crucial roles not only in protection but also in the stability and electrostatic attraction of the ligand to the cavity residues, contributing to a better binding energy [92]. However, the most favored interactions observed in the context of phytopharmaceuticals are observed in Table 3.

Table 3:

Best interactions between complex ligand-protein.

Ligands	Hydrogen Bonds	Pi-cation	Amide-pi Stacked	Van der Wals
Quercetin	Glu A:186, Met A:178, His A:192, Gln A:188, Asp A:193.	Arg A:87.	Thr A:17.	Arg A:116, Asp A:114, Gly A:187, Tyr A:191, Ala A:22,Leu A:113, Ala A: 110, Asp A:132, Gln A:133, Val A:136, Met A:176, Val A:171, Ala A:169, Gly A:191, Asp A:167, Arg A:140.
Fisetin	Arg, A:25, Glu A:186, Arg A:25.	Arg A:87.	Thr A:17.	Gln A: 133, Val A:136, Asp A:132, Ala A:110, Arg A:116, Tyr A:191, Gly A:187, Leu A:113, Ser A:111, Ala A: 22, Asp A:114.
Ellagic Acid	Gln A:188, Ala A:169, Gln A:188.			Asp A:167, Arg A:140, Ala A:168, Gly A:191, Pro A:170, Val A:171, Ala A:189,Ile A:184.
Luteolin	Arg A:35, Tyr A:11, Asp A:30.			Tyr A:75,Leu A:33,Arg A:10,Asp A:76.
Isoharminetin	Arg A:35.	Arg A:35.		Leu A:33,Val A:37,Asp A:76,Arg A:10.

Fonte: BIOVIA, 2024.

Note that not all the interactions are shown in the table, due of course to their limited medicinal use and scope. Some of the interactions are unfavorable for the permanence of the ligand, as can be seen in the interaction between Quercetin (a) and Arg A:25 in Figure 2, which is reddish in color in the 2UYO protein.

This interaction is called Donnor-Donnor and plays a role in repelling the ligand at the hydrogen of the C3′ hydroxyl, and the principle of like repels like applies to this interaction. However, only one Donnor-Donnor interaction is observed in just one of the complexes. Of all the interactions observed in Figure 2, only one covalent interaction between carbon and hydrogen is observed in both complexes, present at residue Gly A: 112. This interaction doesn’t affect anything in the complex, just a classic covalent interaction. However, there is the pi-Alkyl interaction present in both complexes, Quercetin (a) and Fisetin (b), where the pi-Alkyl bond plays a role in strengthening the ligand in the protein through interactions of the pi electrons of an aromatic group on the sigma electrons present in Alkyl groups [92].

For the next complex (Ellagic Acid and Quercetin), the interactions are not very different from the others, except for the number of hydrogen interactions for Quercetin (b), in Figure 3, where the number is greater, a total of four bonds, and the appearance of a pi-sigma interaction (Ala A:168).

The pi-sigma interaction contributes to the stability and positioning of the ligand, as well as contributing to the binding energy [92]. Ellagic Acid (a) does not have any different bonds to the others we have worked on.

For Luteolin (a) in Figure 4, it did not show any more diverse interactions apart from van der Wals interactions and hydrogen bonds; however, Isoharminetin (b) showed an Alkyl interaction in the ether at C1′, as well as the pi-Alkyl interactions and carbon hydrogen bond in the same functional group.

3.5. Comparison of Binding Energies with Drugs That Fight Diseases

During the docking simulations, it is important to compare the results obtained for the ligands with the binding energies of the drugs used to treat the diseases. The drugs that fight the respective bacterial diseases are Rifampicin, Clofazimine, and Dapsone, whose docking was performed on the same targets using the respective protein coordinates; therefore, their Binding Energy results may be different when using other coordinates and proteins. Their respective docking results, together with the results of the best candidates, are denoted in Table 4.

Table 4:

Comparison of the binding energies of Aroeira honey x antibiotics used in the treatment of target diseases.

TARGETS	LIGANDS
	Quercetin	Luteolin	Ellagic Acid	Isoharminetin	Dapsone	Clofazimine	Rifampicin
ML2640c	−8.8	−8.6	−8.1	−8.1	−7.2	−8.4	−6.0
PknA	−8.0	−7.7	−8.3	−7.6	−6.3	−9.4	−7.4
PknB	−7.0	−8.1	−8.1	−8.1	−5.8	−8.2	−7.0

Font: AutoDock Vina, 2024.

The highest-scoring ligands from the Aroeira obtained excellent binding energies in relation to the drugs used in the treatments. This suggests that the ligands could be selected for in vitro and in vivo tests in the future, promoting a great future for the ligands in phytopharmaceutical research and eventually more in-depth and accurate tests of the compounds from the Aroeira-do-Sertão.

About the interactions with the amino acid residues of the control drugs, they were not very different from those commented on the ligands of Aroeira, however, some structures showed some interactions in chlorine and sulfur atoms, as well as many hydrogen interactions can be seen in Supplementary Figures S1–S3, in which all interactions are denoted.

4. Conclusions

Author Contributions

Availability of Data and Materials

Consent for Publication

Conflicts of Interest

Funding

Acknowledgments

References

[1] G.S.M. García, E.A. Souza, V.M. Araújo, M.S.S. Macedo, R.M.A. Andrade, P.R.S. Ferreira, et al., "Território, doenças negligenciadas e ação de agentes comunitários e de combate a endemias" Rev. Saúde Pública, vol. 56, pp. 1-12, 2022. [Crossref] [PubMed]

[2] R.G. Oliveira, "Sentidos das Doenças Negligenciadas na agenda da Saúde Global: O lugar de populações e territórios" Ciência Saúde Coletiva, vol. 23, pp. 2291-2302, 2018. [Crossref] [PubMed]

[3] M.G. Araújo, "Hanseníase no Brasil" Rev. Soc. Bras. Med. Trop., vol. 36, pp. 373-382, 2003. [Crossref] [PubMed]

[4] S.M. Bif, B.W. Braga, J.C. Viana, Z.E.P.T. Silvério, M.B. Azzalin, T.K.F.S. Mendes, et al., "Hanseníase no brasil: Desafios e avanços na prevenção, diagnóstico e tratamento" Braz. J. Implantol. Health Sci., vol. 6, pp. 418-437, 2024. [Crossref]

[5] R.S. Hélio, "Enfoque Clínico da Tuberculose Pulmonar" Clin. Approach Pulm. Tuber. Artigo Orig., vol. 21, pp. 15-18, 2012.

[6] A. Ruffino-Netto, "Tuberculose: A calamidade negligenciada" Rev. Soc. Bras. Med. Trop., vol. 35, pp. 51-58, 2002. [Crossref]

[7] I.M.B. Goulart, "Detecção de TGF-/S1 em Lesões Cutâneas de Diferentes Formas Clínicas de Hanseníase" Master’s Thesis, Universidade Federal de Uberlândia-MG, Uberlândia, Brazil, 1995.

[8] L.A.R. Froes Junior, M.N. Sotto, M.A.B. Trindade, "Hanseníase: Características clínicas e imunopatológicas" An. Bras. Dermatol., vol. 97, pp. 338-347, 2022.

[9] G.O. Penna, M.A.A. Pontes, M.L. Nobre, L.F. Pinto, "Pesquisa Nacional de Saúde revela alto percentual de sinais e sintomas de hanseníase no Brasil" Ciência Saúde Coletiva, vol. 27, pp. 2255-2258, 2022. [Crossref]

[10] L.O. Leão, S.M.R. Silva, M.B.F. Brandão, C.A. Dias, E.T.P. Fernandes, "Representações Sociais do Processo de Diagnóstico e Cura da Hanseníase" Rev. Psicologia Saúde, vol. 12, pp. 73-87, 2019.

[11] V. Eller, L. Alves, S.M. Rodrigues, L. Leão, S. Siqueira, P.H. Ferreira Marçal, "Hanseníase: Aspectos Epidemiológicos, clínicos e diagnósticos" Rev. Cient. FACS, vol. 20, pp. 32-40, 2020.

[12] C.J. Lastória, M.A.M. Abreu, "Hanseníase: Diagnóstico e tratamento" Dermatologia, vol. 17, pp. 173-179, 2012.

[13] M.C.C. Magalhães, L.I. Rojas, "Diferenciação territorial da hanseníase no Brasil" Epidemiologia e Serviços de Saúde, vol. 16, pp. 75-84, 2007.

[14] M.D.P. Silva, P.T. Oliveira, A.A.R. Queiroz, W.A. Alvarenga, "Hanseníase no Brasil: Uma revisão integrativa sobre as características sociodemográficas e clínicas" Res. Soc. Dev., vol. 9, p. e82491110745, 2020. [Crossref]

[15] , "Weekly epidemiological record" Relevé Épidémiologique Hebdomadaire, vol. 98, pp. 409-430, 2023.

[16] R. Fukunaga, P. Glaziou, J.B. Harris, A. Date, K. Floyd, T. Kasaeva, "Epidemiology of Tuberculosis and Progress Toward Meeting Global Targets — Worldwide, 2019" Morb. Mortal. Wkly. Rep., vol. 70, pp. 427-430, 2021. [Crossref] [PubMed]

[17] R. Villar-Hernández, A. Ghodousi, O. Konstantynovska, R. Duarte, C. Lange, M. Raviglione, "Tuberculosis: current challenges and beyond" Breathe, vol. 19, pp. 1-5, 2023. [Crossref]

[18] A. Natarajan, P.M. Beena, A.V. Devnikar, S. Mali, "A systemic review on tuberculosis" Indian J. Tuberc., vol. 67, pp. 295-311, 2020. [Crossref]

[19] D.B. Xavier, "Estudo ecológico de séries temporais das doenças tropicais negligenciadas, malária e tuberculose—Brasil, 2008 a 2030," July 2020.

[20] A.Q. Teixeira, I.C. Samico, A.B. Martins, J.M. Galindo, R.A. Montenegro, H.C. Schindler, "Tuberculose: Conhecimento e adesão às medidas profiláticas em indivíduos contatos da cidade do Recife, Pernambuco, Brasil" Cadernos Saúde Coletiva, vol. 28, pp. 116-129, 2020. [Crossref]

[21] M.E.N. Silva, D.S. Lima, J.E. dos Santos, A.C.F. Cristina, C.M.M. Torquato, V.A. Freire, et al., "Aspectos gerais da tuberculose: Uma atualização sobre o agente etiológico e o tratamento" Rev. RBAC, vol. 50, pp. 228-232, 2018.

[22] , "," in Global Tuberculosis Report, , Eds. Geneva, Switzerland: World Health Organization, 2023, pp. 1-57. Global Report

[23] A.N.A. Propércio, F.A. Oliveira, T.N. Vale, D.R. Bandeira, A.M.S. Marinho, "O Tratamento da Hanseníase a partir de uma Revisão Integrativa" Braz. J. Health Rev., vol. 4, pp. 8076-8101, 2021. [Crossref]

[24] R.A. Yunes, R.C. Pedrosa, V.C. Filho, "Fármacos e fitoterápicos: A necessidade do desenvolvimento da indústria de fitoterápicos e fitofármacos no Brasil" Química Nova, vol. 24, pp. 147-152, 2001. [Crossref]

[25] A.G. Vasconcellos, F.B. Branquinho, C. Sánchez, C.L.S. Lage, "Fitofármaco, fitoterápico, plantas medicinais: O reducionismo e a complexidade na produção do conhecimento científico" Rev. Bras. Farmacognosia, vol. 12, pp. 103-105, 2002. [Crossref]

[26] M.G.M.O. Henriques, A.C. Siani, J.F.G. Pereira, E.S. Pinheiro, "Plantas medicinais e medicamentos fitoterápicos no combate a doenças negligenciadas: Uma alternativa viável?" wwwarcafiocruzbr, vol. 1, pp. 30-35, 2005. [Crossref]

[27] A.S.S. Dutra, R.F.F. Dutra, B.I.L. Cruz, K. Oliveira, L.A. Souza, F.D.M. Marques, et al., "Desafios e inovações na terapêutica de doenças negligenciadas: O papel dos fitoterápicos na busca por soluções eficientes" Braz. J. Implantol. Health Sci., vol. 6, pp. 1967-1994, 2024. [Crossref]

[28] L.O.P. Silva, J.M.R. Nogueira, "Resistência bacteriana: Potencial de plantas medicinais como alternativa para antimicrobianos" Rev. RBAC, vol. 1, pp. 21-27, 2021. [Crossref]

[29] S.C. Argenta, L.C. Argenta, S.R. Giacomelli, V.S. Cezarotto, "Plantas medicinais: cultura popular versus ciência" Vivências Rev. Eletrônica de Extensão da URI, vol. 7, pp. 51-60, 2011.

[30] R.S. Pedroso, G. Andrade, R.H. Pires, "Plantas medicinais: Uma abordagem sobre o uso seguro e racional" Physis Rev. Saúde Coletiva, vol. 31, pp. 1-19, 2021. [Crossref]

[31] I.S.X. França, J.A. Souza, R.S. Baptista, V.R.S. Britto, "Medicina popular: Benefícios e malefícios das plantas medicinais" Rev. Bras. Enfermagem REBEn, vol. 60, pp. 201-208, 2007. [Crossref]

[32] P.V. Rao, K.T. Krishnan, N. Salleh, S.H. Gan, "Biological and therapeutic effects of honey produced by honey bees and stingless bees: A comparative review" Rev. Bras. Farmacogn., vol. 26, pp. 657-664, 2016. [Crossref]

[33] M.A. Mundo, Z.R. Xiong, Y. Galasong, D.C. Manns, T.C. Seeley, A.C. Vegdahl, et al., "Diversity, antimicrobial production, and seasonal variation of honey bee microbiota isolated from the honey stomachs of the domestic honey bee, Apis mellifera" Front. Sustain. Food Syst., vol. 6, 2023. [Crossref]

[34] M.D. Mandal, S. Mandal, "Honey: Its medicinal property and antibacterial activity" Asian Pac. J. Trop. Biomed., vol. 1, pp. 154-160, 2011. [Crossref] [PubMed]

[35] R.A.J. Sacramento, N.F. Duarte, A.H. Araujo, L.A. Ribeiro, E.J.A. Corrêa, "Brazilian Honey and Its Therapeutic Properties," in Honey—Composition and Properties, , Eds. London, UK: IntechOpen, 2022, .

[36] W.G. Lima, J.C.N. Brito, W.S.C. Nizer, D.C.S. Assis, "Antifungal, antibiofilm and anti-resistance activities of Brazilian monofloral honeys against Candida spp." Biocatal. Agric. Biotechnol., vol. 42, 2022. [Crossref]

[37] F.R. Viana, L.S. do Carmo, E.M.A.F. Bastos, "Antibacterial activity of Aroeira honeys produced in Minas Gerais against bacteria of clinical importance" Acta Scientiarum Biol. Sci., vol. 40, pp. 1-4, 2018. [Crossref]

[38] L.C.P. Gardoni, R.M. Santana, J.C.M. Brito, L.X. Ramos, L.A. Araújo, E.M.A.F. Bastos, et al., "Content of phenolic compounds in monofloral aroeira honey and in Floral Nectary Tissue" Pesq. Agropecu. Bras., vol. 57, pp. 1-9, 2022. [Crossref]

[39] W.G. Lima, F.R.S. Santos, V.O. Faria, N.A. Souza, L.P. Souza-Costa, D.C.S. Assis, et al., "Production of a phenolic-rich extract of aroeira honey and characterization of its antimicrobial, antitumoral, and antioxidant activities" Rev. Colomb. Cienc. Quím. Farm., vol. 52, pp. 471-498, 2023. [Crossref]

[40] V.A. Royo, J.S. Cordeiro, P.H.F. Veloso, E.V. Menezes, D.A. Oliveira, A.F.M. Júnior, et al., "Aroeira Honey: New Product for Apitherapy" MINI REVIEW J. Apither., vol. 10, pp. 1-4, 2023.

[41] D.S.P. Júnior, C.A. Almeida, M.C.F. Santos, P.H.V. Fonseca, E.V. Menezes, A.F. de Melo Junior, et al., "Antioxidant activities of some monofloral honey types produced across Minas Gerais (Brazil)" PLoS ONE, vol. 17, 2022.

[42] R. Mărgăoan, E. Topal, R. Balkanska, B. Yücel, T. Oravecz, M. Cornea-Cipcigan, et al., "Monofloral Honeys as a Potential Source of Natural Antioxidants, Minerals and Medicine" Antioxidants, vol. 10, 2021. [Crossref]

[43] A. Daina, O. Michielin, V. Zoete, "SwissADME: A Free web Tool to Evaluate pharmacokinetics, drug-likeness and Medicinal Chemistry Friendliness of Small Molecules" Sci. Rep., vol. 7, 2017. [Crossref]

[44] J. Dulsat, B. López-Nieto, R. Estrada-Tejedor, J.I. Borrell, "Evaluation of Free Online ADMET Tools for Academic or Small Biotech Environments" Molecules, vol. 28, 2023. [Crossref]

[45] G. Bocci, E. Carosati, P. Vayer, A. Arrault, S. Lozano, G. Cruciani, "ADME-Space: A new tool for medicinal chemists to explore ADME properties" Sci. Rep., vol. 7, 2017. [Crossref] [PubMed]

[46] B.B. Petrovska, "Historical review of medicinal plants’ usage" Pharmacogn. Rev., vol. 6, pp. 1-5, 2012. [Crossref]

[47] P.C. Agu, C.A. Afiukwa, O.U. Orji, E.M. Ezeh, I.H. Ofoke, C.O. Ogbu, et al., "Molecular docking as a tool for the discovery of molecular targets of nutraceuticals in disease management" Sci. Rep., vol. 13, 2023. [Crossref]

[48] X.Y. Meng, H.X. Zhang, M. Mezei, M. Cui, "Molecular docking: A powerful approach for structure-based drug discovery" Curr. Comput.-Aided Drug Des., vol. 7, pp. 1-24, 2011. [Crossref]

[49] A.B. Gurung, M.A. Ali, J. Lee, M.A. Farah, K.M. Al-Anazi, "An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19" BioMed Res. Int., vol. 2021, pp. 1-18, 2021. [Crossref] [PubMed]

[50] P.H.M. Torres, A.C.R. Sodero, P. Jofily, F.P. Silva-Jr, "Key Topics in Molecular Docking for Drug Design" Int. J. Mol. Sci., vol. 20, 2019. [Crossref] [PubMed]

[51] K. Nyambo, K.I. Tapfuma, F. Adu-Amankwaah, L. Julius, L. Baatjies, I.S. Niang, et al., "Molecular docking, molecular dynamics simulations and binding free energy studies of interactions between Mycobacterium tuberculosis Pks13, PknG and bioactive constituents of extremophilic bacteria" Sci. Rep., vol. 14, 2024. [Crossref]

[52] A. Ali, G.H. Mir, A. Ayaz, I. Maqbool, S.B. Ahmad, S. Mushtaq, et al., "In silico analysis and molecular docking studies of natural compounds of Withania somnifera against bovine NLRP9" J. Mol. Model., vol. 29, p. 171, 2023. [Crossref]

[53] É.R.A. Sá, A.N. Costa, R.K.M. Costa, J.L. Souza, R.M. Ramos, F.C.A. Lima, "In silico study of the interactions of Pilocarpus microphyllus imidazolic alkaloids with the main protease (M^pro) of SARS-CoV-2" Mol. Simul., vol. 47, pp. 74-87, 2021.

[54] Z. Gerçek, D. Ceyhan, E. Erçağ, "Synthesis and molecular docking study of novel COVID-19 inhibitors" Turk. J. Chem., vol. 45, pp. 704-718, 2021. [Crossref]

[55] E. Oner, I. Demirhan, M. Miraloglu, S. Yalin, E.B. Kurutas, "Investigation of Antiviral Substances in COVID-19 by Molecular Docking: In Silico Study" Afr. Health Sci., vol. 23, pp. 23-36, 2023. [Crossref]

[56] L. Pinzi, G. Rastelli, "Molecular Docking: Shifting Paradigms in Drug Discovery" Int. J. Mol. Sci., vol. 20, 2019. [Crossref] [PubMed]

[57] M. Graña, A. Haouz, A. Buschiazzo, I. Miras, A. Wehenkel, V. Bondet, et al., "The crystal structure of M. leprae ML2640c defines a large family of putative s-adenosylmethionine-dependent methyltransferases in mycobacteria" Protein Sci., vol. 16, pp. 1896-1904, 2009. [Crossref]

[58] S.K. Ravala, S. Singh, G.S. Yadav, S. Kumar, S. Karthikeyan, P.K. Chakraborti, "Evidence that phosphorylation of threonine in the GT motif triggers activation of PknA, a eukaryotic-type serine/threonine kinase from Mycobacterium tuberculosis" FEBS J., vol. 282, pp. 1419-1431, 2015. [Crossref] [PubMed]

[59] T.A. Young, B. Delagoutte, J.A. Endrizzi, A.M. Falick, T. Alber, "Structure of Mycobacterium tuberculosis PknB supports a universal activation mechanism for Ser/Thr protein kinases" Nat. Struct. Mol. Biol., vol. 10, pp. 168-174, 2003. [Crossref] [PubMed]

[60] M. Kashif, N. Subbarao, "Identification of potential novel inhibitors against glutamine synthetase enzyme of Leishmania major by using computational tools" J. Biomol. Struct. Dyn., vol. 41, pp. 13914-13922, 2023. [Crossref] [PubMed]

[61] M. Kashif, S.K. Hira, A. Upadhyaya, U. Gupta, R. Singh, A. Paladhi, et al., "In silico studies and evaluation of antiparasitic role of a novel pyruvate phosphate dikinase inhibitor in Leishmania donovani infected macrophages" Int. J. Antimicrob. Agents, vol. 53, pp. 508-514, 2019. [Crossref] [PubMed]

[62] M. Kashif, A. Paladhi, R. Singh, S. Bhattacharyya, S.K. Hira, P.P. Manna, "Leishmanicidal Activity of an In Silico-Screened Novel Inhibitor Against Ascorbate Peroxidase of Leishmania donovani" Antimicrob. Agents Chemother., vol. 64, p. e01766-19, 2020.

[63] M. Kashif, M. Waseem, N. Subbarao, "In silico prediction of CD8+ and CD4+ T cell epitopes in Leishmania major proteome: Using immunoinformatics" J. Mol. Graph. Model., vol. 129, p. 108759, 2024.

[64] S. Kim, P.A. Thiessen, E.E. Bolton, J. Chen, G. Fu, A. Gindulyte, et al., "PubChem Substance and Compound Databases" Nucleic Acids Res., vol. 44, pp. 1202-1213, 2015. [Crossref]

[65] Y. Xu, S. Wang, Q. Hu, S. Gao, X. Ma, W. Zhang, et al., "CavityPlus: A web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction" Nucleic Acids Res., vol. 46, pp. 374-379, 2018. [Crossref]

[66] E.F. Pettersen, T.D. Goddard, C.C. Huang, G.S. Couch, D.M. Greenblatt, E.C. Meng, et al., "UCSF Chimera—A visualization system for exploratory research and analysis" J. Comput. Chem., vol. 25, pp. 1605-1612, 2004. [Crossref] [PubMed]

[67] O. Trott, A.J. Olson, "AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading" J. Comput. Chem., vol. 31, pp. 455-461, 2010. [Crossref]

[68] G.M. Morris, R. Huey, W. Lindstrom, M.F. Sanner, R.K. Belew, D.S. Goodsell, et al., "AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility" J. Comput. Chem., vol. 30, pp. 2785-2791, 2009. [Crossref]

[69] , "Dessalt Systèmes," in BIOVIA Discovery Studio, , Eds. San Diego, CA, USA: Dessalt Systèmes, 2024, .

[70] D.S. Druzhilovskiy, A.V. Rudik, D.A. Filimonov, T.A. Gloriozova, A.A. Lagunin, A.V. Dmitriev, et al., "Computational Platform Way2Drug: From the Prediction of Biological Activity to Drug Repurposing" Russ. Chem. Bull., vol. 66, pp. 1832-1841, 2017. [Crossref]

[71] J. Ali, P. Camilleri, M.B. Brown, A.J. Hutt, S.B. Kirton, "Revisiting the General Solubility Equation: In Silico Prediction of Aqueous Solubility Incorporating the Effect of Topographical Polar Surface Area" J. Chem. Inf. Model., vol. 52, pp. 420-428, 2012. [Crossref]

[72] H. Tijjani, A. Olatunde, A.P. Adegunloye, A.A. Ishola, "Chapter 14—In silico insight into the interaction of 4-aminoquinolines with selected SARS-CoV-2 structural and nonstructural proteins," in Coronavirus Drug Discovery, C. Egbuna, Eds. Amsterdam, The Netherlands: Elsevier, 2022, pp. 313-333. ScienceDirect

[73] A. Yan, Z. Wang, Z. Cai, "Prediction of Human Intestinal Absorption by GA Feature Selection and Support Vector Machine Regression" Int. J. Mol. Sci., vol. 9, pp. 1961-1976, 2008. [Crossref] [PubMed]

[74] D. Wu, Q. Chen, X. Chen, F. Han, Z. Chen, Y. Wang, "The blood–brain barrier: Structure, regulation, and drug delivery" Signal Transduct. Target. Ther., vol. 8, pp. 1-27, 2023. [Crossref]

[75] I. Hubatsch, E.G.E. Ragnarsson, P. Artursson, "Determination of drug permeability and prediction of drug absorption in Caco-2 monolayers" Nat. Protoc., vol. 2, pp. 2111-2119, 2007. [Crossref]

[76] J.D. Irvine, L. Takahashi, K. Lockhart, J. Cheong, J. Tolan, H.E. Selick, et al., "MDCK (Madin-Darby Canine Kidney) Cells: A Tool for Membrane Permeability Screening" J. Pharm. Sci., vol. 88, pp. 28-33, 1999. [Crossref]

[77] P. Rani, P. Mandal, B.K. Rajak, D.V. Singh, "A review on dynamics of permeability-glycoprotein in efflux of chemotherapeutic drugs" Front. Drug Discov., vol. 4, 2024. [Crossref]

[78] D.N. Thomas, J.W. Wills, H. Tracey, S.J. Baldwin, M. Burman, A.N. Williams, et al., "Ames test study designs for nitrosamine mutagenicity testing: qualitative and quantitative analysis of key assay parameters" Mutagenesis, vol. 39, pp. 78-95, 2024. [Crossref] [PubMed]

[79] V. Goyal, M. Bandari, "Rodents in Drug Discovery," in Rodents and Their Role in Ecology, Medicine and Agriculture, M.M. Shah, Eds. London, UK: IntechOpen, 2023, p. 98.

[80] , "," in Relatório das Análises de Composição de Méis, , Eds. Salvador, Brazil: Companhia de Desenvolvimento e Ação Regional, 2022, pp. 1-22.

[81] J.V. MadeiraJ.V. Madeira, "Potencial do Mel de Aroeira como Conservante de Alimentos: Atividades Antioxidante e Antibacteriana. [Trabalho de Conclusão de Curso], Universidade Federal de Ouro Preto Escola de Nutrição Colegiado de Ciência e Tecnologia de Alimentos, Ouro Preto, Brazil" Available online: www.monografias.ufop.br. (accessed on 22 July 2024)

[82] A. Ullah, S. Munir, S.L. Badshah, N. Khan, L. Ghani, B.G. Poulson, et al., "Important Flavonoids and Their Role as a Therapeutic Agent" Molecules, vol. 25, 2020. [Crossref] [PubMed]

[83] A. Roy, A. Khan, I. Ahmad, S. Alghamdi, B.S. Rajab, A.O. Babalghith, et al., "Flavonoids: A Bioactive Compound from Medicinal Plants and Its Therapeutic Applications" BioMed Res. Int., vol. 2022, 2022. [Crossref]

[84] J.M. Al-Khayri, G.R. Sahana, P. Nagella, B.V. Joseph, F.M. Alessa, M.Q. Al-Mssallem, "Flavonoids as Potential Anti-Inflammatory Molecules: A Review" Molecules, vol. 27, 2022. [Crossref]

[85] A.N. Panche, A.D. Diwan, S.R. Chandra, "Flavonoids: An Overview" J. Nutr. Sci., vol. 5, p. e47, 2016. [Crossref]

[86] S. Kumar, A.K. Pandey, "Chemistry and Biological Activities of Flavonoids: An Overview" Sci. World J., vol. 2013, p. 162750, 2013. [Crossref]

[87] L.A. Khawli, S. Prabhu, "Drug Delivery across the Blood–Brain Barrier" Mol. Pharm., vol. 10, pp. 1471-1472, 2013. [Crossref]

[88] D.A. Volpe, "Drug-permeability and transporter assays in Caco-2 and MDCK cell lines" Future Med. Chem., vol. 3, pp. 2063-2077, 2011. [Crossref] [PubMed]

[89] N.N. Wang, J. Dong, Y.H. Deng, M.F. Zhu, M. Wen, Z.J. Yao, et al., "ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting" J. Chem. Inf. Model., vol. 56, pp. 763-773, 2016. [Crossref]

[90] H. Fokoue, P. Pinheiro, C. Fraga, C. Sant’Anna, "Há Algo Novo no Reconhecimento Molecular Aplicado à Química Medicinal?" Química Nova, vol. 43, pp. 78-89, 2020. [Crossref]

[91] J.N. Israelachvili, "Van der Waals Forces Between Particles and Surfaces," in Intermolecular and Surface Forces, , Eds. Amsterdam, The Netherlands: Elsevier BV, 2011, pp. 253-289.

[92] M.W. Krone, C.R. Travis, G.Y. Lee, H.J. Eckvahl, K.N. Houk, M.L. Waters, "More Than π–π–π Stacking: Contribution of Amide−π and CH−π Interactions to Crotonyllysine Binding by the AF9 YEATS Domain" J. Am. Chem. Soc., vol. 142, pp. 17048-17056, 2020. [Crossref] [PubMed]