The study addresses the considerable socio-economic burden posed by the inflammatory autoimmune disease rheumatoid arthritis, affecting around 1% of the global population (Smolen et al., 2016). Acknowledging the limitations of current RA treatments, the research aims to explore alternative therapeutic interventions with reduced side effects. The principal focus is on investigating the potential of phytochemicals to target the cytokine TNF-α, thereby demonstrating their anti-inflammatory activity.
In pursuit of identifying active chemical constituents of Aloe vera possessing potential interactions with the TNF alpha protein, molecular docking studies were conducted for a set of 74 Aloe vera chemical constituents. The subsequent identification of top hits is discussed herein. Moreover, our investigation extended to assessing the pharmacokinetics and toxicity properties of molecules exhibiting promising results, positioning them as potential drug candidates. The use of Autodock Vina facilitated the determination of molecular interactions and binding energy between Aloe vera phytoconstituents and TNF alpha protein, contributing valuable insights for drug discovery endeavours. Aloe vera demonstrates anti-inflammatory properties by effectively inhibiting the cyclooxygenase pathway, resulting in a diminished synthesis of prostaglandins and, consequently, a reduction in inflammatory processes (Devaraj and Karpagam, 2011; Vijayalakshmi et al., 2012). The bioactive compounds in Aloe vera demonstrate an inhibitory effect on the release of pro-inflammatory mediators, such as cytokines and histamine (Arunkumar and Muthuselvam, 2009; Jalinder et al., 2022; Kumar et al., 2019).
Binding energy is a measure of the affinity in a ligand-protein complex. It represents the difference between the energy of the complex (ligand bound to the protein) and the sum of the energies of each molecule separately (ligand and protein considered as independent entities). In other words, it quantifies the stability and strength of the interaction between the ligand and the protein in a molecular complex. A lower binding energy typically indicates a more favourable and stronger binding interaction (Kastritis and Bonvin, 2013). Table 2 displays the binding potential energy or Vina fitness scores resulting from the docking of TNF-α with both approved drugs and Aloe vera compounds. A comparison of the docked binding energies of the best ligands with reference standard drugs indicates that the drugs exhibit lower binding energies than the top 10 ligands. The observed binding affinity values range from − 10 to -9.1 kcal/mol (Table 2). Notably, mannan emerges as the highest binding affinity compound, registering − 10 kcal/mol, surpassing folacin, aloesin, beta-sitosterol and other compounds. Analysis of the docking results, the interactions listed in Table 2 reveal that the biochemical compounds in Aloe vera exhibit highly consistent interactions, surpassing aspirin and other drug standards. Consequently, mannan, folacin, and aloesin are identified as the top three most promising inhibitors of TNF-α.
Table 1
Characteristics of phytoconstituents of Aloe vera (L)
S.No. | Ligand | PubChem ID | Molecular formula | Molecular weight (g/mol) |
1. | 2(3H)-Benzothiazolone | 13625 | C7H5NOS | 151.19 |
2. | 3,4-Dihydrocoumarin | 660 | C9H8O2 | 148.16 |
3. | 7-Hydroxy-4-benzopyrone | 5409279 | C9H6O3 | 162.14 |
4. | 15-Methylhexadecanoic acid | 164860 | C17H34O2 | 270.5 |
5. | Acemannan | 72041 | C66H100NO49− | 1691.5 |
6. | Allantoin | 204 | C4H6N4O3 | 158.12 |
7. | Aloe emodin | 10207 | C15H10O5 | 270.24 |
8. | Aloenin | 162305 | C19H22O10 | 410.4 |
9. | Aloeresin | 160190 | C19H22O9 | 394.4 |
10. | Aloesone | 5317700 | C13H12O4 | 232.23 |
11. | Aloin A | 12305761 | C21H22O9 | 418.4 |
12. | Aloin B | 14989 | C21H22O9 | 418.4 |
13. | Aluminum | 5359268 | Al | 26.981 |
14. | anthracene | 8418 | C14H10 | 178.23 |
15. | anthranol | 10731 | C14H10O | 194.23 |
16. | Anthraquinone | 6780 | C14H8O2 | 208.21 |
17. | Ascorbic Acid | 54670067 | C6H8O6 | 176.12 |
18. | Asparagine | 6267 | C4H8N2O3 | 132.12 |
19. | Aspirin | 2244 | C9H8O4 | 180.16 |
20. | Auxin | 802 | C10H9NO2 | 175.18 |
21. | beta carotene | 5280489 | C40H56 | 536.9 |
22. | beta sitosterol | 222284 | C29H50O | 414.7 |
23. | Campesterol | 173183 | C28H48O | 400.7 |
24. | Carvacrol | 10364 | C10H14O | 150.22 |
25. | Caryophyllene oxide | 1742210 | C15H24O | 220.35 |
26. | Caryophyllene | 5281515 | C15H24 | 204.35 |
27. | Celecoxib | 2662 | C17H14F3N3O2S | 381.4 |
28. | Cholesterol | 5997 | C27H46O | 386.7 |
29. | Chrysophanic acid | 10208 | C15H10O4 | 254.24 |
30. | chrysophanol | 10208 | C15H10O4 | 254.24 |
31. | Citric acid | 311 | C6H8O7 | 192.12 |
32. | Creatinine | 588 | C4H7N3O | 113.12 |
33. | Cycloartenol | 92110 | C30H50O | 426.7 |
34. | Cysteine hydrochloride | 25150 | C3H8ClNO2S | 157.62 |
35. | Cysteine | 5862 | C3H7NO2S | 121.16 |
36. | D fructose | 2723872 | C6H12O6 | 180.16 |
37. | D galactonic acid | 128869 | C6H12O7 | 196.16 |
38. | D galactose | 6036 | C6H12O6 | 180.16 |
39. | D glucose | 5793 | C6H12O6 | 180.16 |
40. | D mannose | 18950 | C6H12O6 | 180.16 |
41. | d Tartaric acid | 439655 | C4H6O6 | 150.09 |
42. | Danshenxinkun A | 149138 | C18H16O4 | 296.3 |
43. | Danthron | 2950 | C14H8O4 | 240.21 |
44. | Docosane | 12405 | C22H46 | 310.6 |
45. | elgonica dimer A | 21582596 | C36H30O14 | 686.6 |
46. | Feralolide | 5317333 | C18H16O7 | 344.3 |
47. | Folacin | 135398658 | C19H19N7O6 | 441.4 |
48. | Galactomannan | 439336 | C18H32O16 | 504.4 |
49. | Globulin G | 74329879 | C36H61N7O19 | 895.9 |
50. | Hydrocortisone | 5754 | C21H30O5 | 362.5 |
51. | Ibuprofen | 3672 | C13H18O2 | 206.28 |
52. | Isoaloeresin | 76332505 | C29H32O11 | 556.6 |
53. | kaempferol | 5280863 | C15H10O6 | 286.24 |
54. | L Arabinose | 439195 | C5H10O5 | 150.13 |
55. | Leucine | 6106 | C6H13NO2 | 131.17 |
56. | linalool | 6549 | C10H18O | 154.25 |
57. | Lophenol | 160482 | C28H48O | 400.7 |
58. | Lupeol | 259846 | C30H50O | 426.7 |
59. | Mannan | 25147451 | C24H42O21 | 666.6 |
60. | Meloxicam | 54677470 | C14H13N3O4S2 | 351.4 |
61. | Naproxen | 156391 | C14H14O3 | 230.26 |
62. | Niacin | 938 | C6H5NO2 | 123.11 |
63. | Phenylalanine | 6140 | C9H11NO2 | 165.19 |
64. | Potassium | 5462222 | K | 39.098 |
65. | Proline | 145742 | C5H9NO2 | 115.13 |
66. | Quercetin | 5280343 | C15H10O7 | 302.23 |
67. | Rhababerone | 12310964 | C15H10O5 | 270.24 |
68. | Salicylic acid | 338 | C7H6O3 | 138.12 |
69. | Serine | 5951 | C3H7NO3 | 105.09 |
70. | Sorbitol | 5780 | C6H14O6 | 182.17 |
71. | Spathulenol | 92231 | C15H24O | 220.35 |
72. | Threonine | 6288 | C4H9NO3 | 119.12 |
73. | Thymol acetate | 68252 | C12H16O2 | 192.25 |
74. | Tricosane | 12534 | C23H48 | 324.6 |
Table 2
Molecular Docking Results of Aloe vera Compounds against TNF alpha and the interacting amino acids
Compound Name | Docking Score (Kcal/mol) | Amino acids with hydrogen bonds | Amino acids with hydrophobic Interactions |
Drug references | |
Aspirin | -5.6 | GLN 102B | GLN 102A |
Celecoxib | -7.6 | ARG 103B, GLU 104B | GLN 102A, GLN 102B, GLN 102C, GLU 104A |
Hydrocortisone | -6.3 | ALN 33A, ASN 34A, ARG 82C | |
Ibuprufen | -6.5 | TYR 115A, SER 99C, CYS 101A | PRO 100A |
Meloxicam | -6.3 | ARG 103C, GLU 104A, GLU 104B, GLU 104C, GLN 102B, ARG 103A | ARG 103B |
Naproxen | -7.1 | LYS 65B, LEU 142B | PHE 144B |
Aloe vera Compounds | |
Mannan | -10 | PRO 100C, GLN 102B, ARG 103B, GLN 102A, PRO 100°, GLU 116B | GLU 116C, ARG 103°, GLU 104C, PRO 100B |
Folacin | -9.8 | SER 99B, SER 99C GLU 116B, GLN 102A | GLN 102C, GLU 116A |
Aloesin | -9.8 | ALA 22B, GLY 24B, LYS 65B, ASP 140B | - |
Beta sitosterol | -9.6 | GLU 116C, LYS 98B | ARG 103B |
Campesterol | -9.6 | GLU 116B | ARG 103B |
Lophenol | -9.4 | GLU 116A | ARG 103B |
Galactomannan | -9.4 | THR 105B, ARG 103B, ARG 103A, GLN 102A, GLN 102B, GLU 104A, GLU 104B | GLU 107B |
Cholesterol | -9.3 | GLU 116B, LYS 98C | ARG 103B, LYS 98B |
Quercetin | -9.1 | GLN 102A, PRO 100A, GLU 116C, GLN 102C | |
Kaempferol | -9.1 | ASN 34A, GLN 125C, THR 7A, LEU 37A | LEU 36A |
In-depth scrutiny of the results highlights that mannan achieves the lowest binding energy (-10 kcal/mol) in complex with 1TNF, presenting the best score among the docked compounds. However, it's important to note that mannan exhibits three violations of Lipinski's rule of five (Table 3). Conversely, aloesin, in docking with the main protease, demonstrates an affinity of -9.8 kcal/mol and forms four hydrogen bonds with ALA 22B, GLY 24B, LYS 65B, and ASP 140B. Notably, aloesin complies with Lipinski's rule of five without any violation, emphasizing its favourable drug-like properties.
Table 3
Lipinski parameters for dataset from SwissADME
Code | Compound | Molecular weight (Da) | Log p | HBD | HBA | Violation | Yes/No | Solubility | Log S(Mol/L) |
1 | Mannan | 666.58 | 0.53 | 14 | 21 | 3 | No | Highly soluble | 2.5 |
2 | Folacin | 441.4 | 0.04 | 6 | 9 | 2 | No | Soluble | -2.91 |
3 | Aloesin | 394.37 | 0.92 | 5 | 9 | 0 | Yes | Very soluble | -1.53 |
4 | Beta sitosterol | 414.71 | 5.05 | 1 | 1 | 1 | Yes | Poorly soluble | -9.67 |
5 | Campesterol | 400.68 | 4.97 | 1 | 1 | 1 | Yes | Poorly soluble | -9.11 |
6 | Lophenol | 400.68 | 5.06 | 1 | 1 | 1 | Yes | Poorly soluble | -9.02 |
7 | Galactomannan | 504.44 | 0.13 | 11 | 16 | 3 | No | Highly soluble | 1.38 |
8 | Cholesterol | 386.65 | 4.89 | 1 | 1 | 1 | Yes | Poorly soluble | -9.02 |
9 | Quercetin | 302.24 | 1.63 | 5 | 7 | 0 | Yes | Soluble | -3.91 |
10 | Kaempferol | 286.24 | 1.70 | 4 | 6 | 0 | Yes | Soluble | -3.86 |
The stability of the ligand-receptor complex is attributed to hydrogen bonds formed by OH and C = O groups, with the ligand playing a dual role as acceptor and donor (Matondo et al., 2018). This interaction, coupled with dispersion forces (Trujillo and Sánchez-Sanz, 2016), π--π interactions (Kasende et al., 2017), and hydrophobic interactions (Muya et al., 2019), particularly involving polar amino acids, contributes to the overall stability of the complex.
Prediction of drug-likeness descriptors and toxicity
The selection of potential inhibitors or optimal docked ligands was based on their binding energy, a critical factor in determining their efficacy. However, in the context of drug development, the evaluation of ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties is essential. The assessment of physicochemical properties, a key parameter influencing efficacy, safety, and metabolism, was carried out employing appropriate methodologies, emphasizing the significance of these properties in the drug development and discovery processes (Pires et al., 2015; Clark,2005).
In evaluating the physicochemical properties using Lipinski's rule of five (RO5), which includes criteria such as molecular mass, hydrogen-bond donors, hydrogen-bond acceptors, and Log P, the results demonstrated that among the top ten ligands, only 3 ligands fully complied with Lipinski's rule. Lipinski's screening serves as a crucial filter in the drug design process, determining the suitability of a compound for further development (Lipinski, 2004).
The polysaccharides mannan and galactomannan, along with the steroids Campasterol, β-sitosterol, cholesterol, and lophenol, exhibited a noteworthy affinity for TNF-α. However, their potential use as drugs is hindered by a failure to comply with essential pharmacological parameters and a violation of the Lipinski rule of drug-likeness (Daina et al., 2017).
In contrast, the chromone aloesin, and the flavonoids Quercetin and Kampferol, emerged as promising TNF-α inhibitors. These compounds not only demonstrated high affinity but also met all pharmacological parameters, showing potential for effective drug development. The binding energies of aloesin, Quercetin, and Kampferol were found to be -9.8, -9.1, and − 9.1 kcal/mol, respectively (Table 2). Importantly, these compounds adhered to pharmacological rules and displayed lead-like properties, as outlined in Table 3. This suggests a potential avenue for the development of these phytochemicals into drug molecules specifically targeting the cytokine TNF-α, which is in line with previous studies highlighting the anti-inflammatory properties of these compounds (Deng et al., 2020; Loke et al., 2008; Barron et al., 2021; Yagi and Takeo,2003).
Table 4 presents the pharmacokinetic and toxicity properties of the three potential inhibitors: mannan, folacin, and aloesin. The Ames test, assessing mutagenicity, indicates that all three ligands are non-mutagenic. Carcinogenicity in rats (Carcino_Rat) is negative for all ligands, suggesting no carcinogenic potential. None of the ligands are predicted to permeate the blood-brain barrier (BBB non-permeant). Mannan and folacin show hERG I inhibition, indicating a potential risk for cardiac arrhythmia, while aloesin does not inhibit hERG I. All ligands are non-substrates for P-glycoprotein (P-gp S.), suggesting a low likelihood of causing drug interactions related to P-gp. Folacin and aloesin are predicted to have hepatotoxicity, while mannan is not. None of the ligands show skin sensitization. Regarding cytochrome P450 inhibition, all ligands exhibit no inhibitory effects on the assessed isoforms (1A2, 2C19, 2C9, 2D6, 3A4). Overall, these results suggest that aloesin demonstrates a more favourable toxicity profile compared to mannan and folacin, making it a promising candidate for further drug development (Yagi and Takeo, 2003).
Table 4
Pharmacokinetics and toxicity properties of the three potential inhibitors
Ligand | Ames_test | Carcino_Rat | BBB permeant | hERG I | hERG II | P-gp S. | Hepatotoxicity | Skin sensitization | 1A2 | 2C19 | 2C9 | 2D6 | 3A4 |
Mannan | No | Negative | No | No | Yes | Yes | No | No | No | No | No | No | No |
Folacin | No | Negative | No | No | No | No | Yes | No | No | No | No | No | No |
Aloesin | No | Negative | No | No | No | No | Yes | No | No | No | No | No | No |
Future Directions:
In vitro and in vivo experimental validation: Conduct cell-based assays using inflammatory cell lines (e.g., RAW 264.7 macrophages) to evaluate the inhibitory effects of aloesin, quercetin, and kaempferol on TNF-α production and other inflammatory mediators. Subsequently, preclinical studies using animal models of RA (e.g., collagen-induced arthritis in mice) should be performed to assess the compounds' anti-inflammatory and therapeutic efficacy in vivo.
Compound optimization and structure-activity relationship (SAR) studies: Employ medicinal chemistry techniques, such as structural modifications and analog synthesis, to optimize the identified compounds for improved potency, selectivity, and pharmacokinetic properties. SAR analyses will aid in identifying the structural features crucial for biological activity and guide the design of more potent analogs.
Preclinical toxicology and pharmacokinetic studies: Perform comprehensive in vivo toxicity studies (e.g., acute and chronic toxicity, genotoxicity, and reproductive toxicity) to establish the safety profiles of the optimized compounds. Pharmacokinetic studies, including absorption, distribution, metabolism, and excretion (ADME) analyses, will provide insights into the compounds' bioavailability and clearance, informing dosing regimens for future clinical trials.
Clinical translation: Based on the outcomes of preclinical studies, initiate Phase I clinical trials to evaluate the safety and tolerability of the lead compounds in healthy volunteers, followed by Phase II and Phase III trials to assess their efficacy and effectiveness in patients with rheumatoid arthritis. These trials should be designed in accordance with regulatory guidelines and ethical principles, with careful monitoring of adverse events and clinical outcomes.