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Deciphering the multi-target anticancer potential of β-sitosterol in breast cancer through integrated computational
Alma Khan1, Srinivas Ganjipete2, Prabu Kumar Seetharaman3
1Department of Pharmacology, Faculty of Pharmacy, M.S. Ramaiah University of Applied Sciences, Bengaluru, Karnataka 560054, India.
Abstract:
Breast cancer is a complex disease comprising multiple deregulated signaling pathways, oxidative stress, metabolic rewiring, and resistance to therapy. The multi-target therapeutic efficacy of β-sitosterol against breast cancer was studied using an integrated approach that combined network pharmacology, molecular docking, molecular dynamics simulations, and ADMET. Out of which 98 common targets were identified between β-sitosterol and breast cancer, wherein PPARG, TNF, ABL kinase, HIF1A, ESR1, PGR, PPARA, MAPK8, AR, and ESR2 are the key hub genes. The enrichment analysis showed that β-Sitosterol had strong binding affinities towards ABL kinase (-9.7 kcal/mol), PPARA (-9.5 kcal/mol), MAPK8 (-8.7 kcal/mol), and PPARG (-8.6 kcal/mol). Indeed, molecular dynamics simulations were performed for 1000 ns at the molecular level, and the progesterone receptor (PGR) proved to be the most dynamically stable target, as the β-sitosterol-PGR complex remained stable throughout the simulation. The predicted ADMET profile was good. The results suggest that β-sitosterol acts on multiple targets in breast cancer and identify PGR, a target not strongly favored by docking alone, as an important therapeutic target revealed through extended molecular dynamics simulation.
Insights
Beta-sitosterol shows multi-target therapeutic potential against breast cancer by interacting with key genes like PPARG and PGR. Molecular dynamics simulations highlight the progesterone receptor (PGR) as a key stable target for beta-sitosterol in breast cancer therapy.
Area of Science:
- Oncology
- Pharmacology
- Computational Biology
Background:
- Breast cancer involves complex signaling pathways, oxidative stress, metabolic changes, and therapy resistance.
- Beta-sitosterol is a phytosterol with potential anti-cancer properties.
Purpose of the Study:
- To investigate the multi-target therapeutic efficacy of beta-sitosterol against breast cancer using an integrated computational approach.
- To identify key molecular targets and pathways affected by beta-sitosterol in breast cancer.
Main Methods:
- Network pharmacology to identify common targets between beta-sitosterol and breast cancer.
- Molecular docking and molecular dynamics simulations to assess binding affinities and complex stability.
- ADMET prediction to evaluate pharmacokinetic properties.
Main Results:
- Identified 98 common targets, with PPARG, TNF, ABL kinase, HIF1A, ESR1, PGR, PPARA, MAPK8, AR, and ESR2 as key hub genes.
- Beta-sitosterol exhibited strong binding affinities for ABL kinase, PPARA, MAPK8, and PPARG.
- Molecular dynamics simulations revealed the progesterone receptor (PGR) as a highly stable target for beta-sitosterol.
Conclusions:
- Beta-sitosterol demonstrates multi-target therapeutic effects on breast cancer.
- The progesterone receptor (PGR) is identified as a significant therapeutic target for beta-sitosterol in breast cancer, particularly revealed through molecular dynamics simulations.
- The favorable predicted ADMET profile suggests potential clinical applicability.
