Algal Research, Год журнала: 2024, Номер 84, С. 103768 - 103768
Опубликована: Окт. 22, 2024
Язык: Английский
South African Journal of Botany, Год журнала: 2025, Номер 178, С. 348 - 359
Опубликована: Фев. 6, 2025
Язык: Английский
Процитировано
0
Journal of Ethnopharmacology, Год журнала: 2025, Номер unknown, С. 119380 - 119380
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
0
International Journal of Applied Pharmaceutics, Год журнала: 2025, Номер unknown, С. 51 - 60
Опубликована: Фев. 24, 2025
Objective: Cancer involves uncontrolled cell growth and spreading to other body parts. Lung cancer is the most common deadliest worldwide, with treatments often causing significant side effects. This research aims predict potential of compounds in mangosteen (Garcinia mangostana L.) as a candidate for lung therapy. Methods: The methods used this are network pharmacology analysis using string cytoscape, molecular docking deep learning, dynamics simulations. Results: Eleven have been identified Garcinia L., including catechin, gartanin, alpha-mangostin, norathyriol, maclurin, 8-deoxygartanin, beta-mangostin, gamma-mangostin, garcinone A, B, D. Based on ADMET analysis, these exhibit varying degrees absorption, distribution, metabolism, excretion, toxicity profiles, which can provide valuable insights into their therapeutic applications safety profiles. It has protein targets AURKA, PLK1, CCNA2, KIF11, AURKA chosen Molecular revealed D binding energy-10.30 kcal/mol gamma-Mangostin-10.28 had better affinity than native ligand adenosine-5'-diphosphate-9.00 kcal/mol. simulations indicated that gamma-Mangostin were less stable over 100 ns simulation. Conclusion: compounds, D, target cancer-related demonstrate affect key biological pathways such cycle motor proteins. Deep learning shows gamma-mangostin high affinity, while confirm stability ns.
Язык: Английский
Процитировано
0
Algal Research, Год журнала: 2024, Номер 84, С. 103768 - 103768
Опубликована: Окт. 22, 2024
Язык: Английский
Процитировано
0