Insights into Metabolites Profiling and Pharmacological Investigation of Aconitum heterophyllum wall ex. Royle Stem through Experimental and Bioinformatics Techniques

Abstract

The Aconitum genus is a leading source of a wide range of structurally diverse metabolites with significant pharmacological implications. The present study investigated metabolite profiling, pharmacological investigation, anticancer potential, and molecular docking analysis of the stem part of Aconitum heterophyllum (AHS). The metabolite profiling of the AHS extract was experimentally examined using LC-MS/MS-orbitrap in both modes (ESI⁺/ESI^-) and GC-MS in EI mode. The in vitro MTT model was used to study the anticancer potential, while the in vivo animal model was used to study the anti-inflammatory and antinociceptive activities. The MOE software was used for the molecular docking study. A total of 118 novel and previously known metabolites, among 44 metabolites (26 in ESI⁺ positive mode and 18 in ESI^- negative mode) in the MeOH extract, while 74 metabolites (46 in ESI⁺ and 28 in ESI^- mode) were identified in the n-hexane extract via LCMS/MS. The identified metabolites include 24 phenolic compounds, 18 alkaloids, 10 flavonoids, 24 terpenoids, 2 coumarins, 2 lignans, and 38 other fatty acids and organic compounds. The major bioactive metabolites identified were hordenine, hernagine, formononetin, chrysin, N-methylhernagine, guineesine, shogaol, kauralexin, colneleate, zerumbone, medicarpin, boldine, miraxinthin-v, and lariciresinol-4-O-glucoside. Furthermore, the GC-MS study helped in the identification of volatile and nonvolatile chemical constituents based on the mass spectrum and retention indices. The methanol extract significantly inhibited tumor progression in H9c2 and MDCK cancer cells with IC₅₀ values of 186.39 and 199.63 μg/mL. In comparison, the positive control aconitine exhibited potent IC₅₀ values (132.32 and 141.58 μg/mL) against H9c2 and MDCK cell lines. The anti-inflammatory (carrageenan-induced hind paw edema) and antinociceptive (acetic acid-induced writhing) effects were significantly dose-dependent, (p < 0.001) and (p < 0.05), respectively. In addition, a molecular docking study was conducted on identified ligands against the anti-inflammatory enzyme (COX-2) (PDB ID: 5JVZ) and the cancer enzyme ADAM10 (PDB ID: 6BDZ) which confirmed the anti-inflammatory and anticancer effects in an in silico model. Among all ligands, L2, L3, and L7 exhibit the most potent potential for inhibiting COX-2 inflammation with binding energies of -7.3424, -7.0427, and -8.3562 kcal/mol. Conversely, against ADAM10 cancer protein, ligands L1, L4, L6, and L7, with binding energies of -8.0650, -7.7276, -7.0454, and -7.2080 kcal/mol, demonstrated notable effectiveness. Overall, the identified metabolites revealed in this AHS research study hold promise for discovering novel possibilities in the disciplines of chemotaxonomy and pharmacology.

Figure 1

LC-MS/MS-orbitrap metabolites profiling of AHS methanol extract in ESI ⁺ mode (red) and ESI^– mode (green). A total ion chromatogram (TIC) in both positive and negative ions based on UPLC-ESI-MS/MS analysis.

Figure 2

LC-MS/MS-orbitrap metabolites profiling of AHS n-hexane extract in ESI ⁺ mode (red), and ESI^– mode (green). A total ion chromatogram (TIC) was performed in both positive and negative ions based on UPLC-ESI-MS/MS analysis.

Figure 3

GC-MS phytochemical profiling of methanol (A) and n-hexane (B) extracts of AHS. A total ion chromatogram (TIC) was obtained via gas chromatography mass spectrometry electron ionization (GC-MS-EI) analysis.

Figure 4

Percent cell viability of various cancer cell lines at different doses of methanol and n-hexane stem extracts of A. heterophyllum. Note. M: Methanol extract, H:n-Hexane extract. Statistically data were analyzed through one-way ANOVA followed by multiple-comparison test (Dunnett’s test). Values with distinct letters are significantly different from each other (p > 0.05).

Figure 5

Comparative representation of % cell between cancer cell lines at different doses of methanol, n-hexane stem extracts, and Aconitine (standard drug).

Figure 6

Antinociceptive activity of AHS (A) methanol and (B) n-hexane extracts (50–200 mg/kg). The percentage inhibition of writhing responses was calculated in comparison with the control with the vehicle (5% DMSO, 1% Tween80). The positive control (DS), administered at a dose of 10 mg/kg, resulted in the significant reduction of the number of writhes to 68.15%. Values with distinct letters are significantly different from each other (p ≤ 0.05).

Figure 7

Anti-inflammatory activity of AHS methanol and n-hexane extracts (50–200 mg/kg). One-way ANOVA was conducted followed by posthoc analysis using Dunnett’s test. Each value was expressed as mean ± SEM (n = 3). Differences from the control group, Diclofenac sodium were determined by ANOVA followed by Dunnett’s test. Significance was assumed as p ≤ 0.05(****), p ≤ 0.04(**), p ≤ 0.03(*) versus Diclofenac sodium.

Figure 8

Molecular docked-pose of best docked phytocompounds (ligands) of A. heterophyllum stem against protein (COX-2, PDB-ID: 5JVZ): (A) 3D structures of 5JVZ enzyme (B) 2D interaction of L1 = Chrysin, compound CID: 5281607 and L7 = Guineesine, compound CID: 6442405 with interacting amino acids of 5JVZ; (C) 3D interactions of L1 and L7 with enzymes 5JVZ. Note: L = Ligands.

Figure 9

Molecular docked-pose of best docked phytocompounds (ligands) of A. heterophyllum stem against protein (ADAM10, PDB-ID: 6BDZ): (A) 3D structures of 6BDZ enzyme (B) 2D interactions of L1 = Chrysin, compound CID: 5281607, L4 = Formononetin, compound CID: 5280378 and L7 = Guineesine, compound CID: 6442405) with interacting amino acids of 6BDZ; (C) 3D interaction of L1, L4, and L7 with enzymes 6BDZ. Note: L = Ligands.