Neuropharmacological and antiproliferative activity of Tetrastigma leucostaphyllum (Dennst.) Alston: Evidence from in-vivo, in-vitro and in-silico approaches.
Saudi Pharm J
; 31(6): 929-941, 2023 Jun.
Article
en En
| MEDLINE
| ID: mdl-37234345
As the incidence of neurodegeneration and cancer fatalities remains high, researchers are focusing their efforts on discovering and developing effective medications, especially plant-based drugs, against these diseases. Hence, this research aimed to investigate the neuropharmacological potentials of aerial parts of Tetrastigma leucostaphyllum, employing some behavioral models, while the antiproliferative effect was explored against a panel of cancer cell lines (MGC-803, A549, U-251, HeLa and MCF-7) using a colorimetric assay. In addition, active extracts were analyzed by GC-MS technique to identify the active compounds, where some selective compounds were docked with the particular pure proteins to check their binding affinity. Results from neuropharmacological research indicated that the total extract and its fractions may be effective (p = 0.05, 0.01, and 0.001, respectively) at doses of 100, 200, and 400 mg/kg of animal body weight. The greatest antidepressant and anxiolytic effects were found in the n-hexane fraction. The n-haxane fraction also exhibited the highest cytotoxicity against the U-251 cell line (IC5014.3 µg/mL), followed by the A549, MG-803, HeLa, and MCF-7 cell lines, respectively. From the n-hexane fraction, ten chemicals were detected using the GC-MS method. Additionally, the in-silico research revealed interactions between the n-hexane fractions' identified compounds and the antidepressant, anxiolytic, and cytotoxic receptors. The molecules showed binding affinities that ranged from 4.6 kcal/mol to 6.8 kcal/mol, which indicates the likelihood that they would make good drug candidates. This study highlighted the plant's neuropharmacological and cytotoxic properties, however, more research is needed to determine the etymological origin of these effects.
Texto completo:
1
Banco de datos:
MEDLINE
Idioma:
En
Año:
2023
Tipo del documento:
Article