Network pharmacology research integrating LC–MS/MS, machine learning, molecular docking, and dynamics simulation: key biomarkers and potential mechanisms of Phellinus igniarius against prostate cancer | Synapse
March 3, 2026Open Access
Network pharmacology research integrating LC–MS/MS, machine learning, molecular docking, and dynamics simulation: key biomarkers and potential mechanisms of Phellinus igniarius against prostate cancer
Key Points
Key biomarkers were identified that may influence prostate cancer outcomes, emphasizing the potential of traditional remedies.
The analysis utilized molecular docking and dynamics simulation to explore interactions at the cellular level for therapeutic insights.
This research integrates network pharmacology with machine learning techniques, providing a comprehensive understanding of potential treatment pathways.
The findings may enable novel approaches for prostate cancer therapies, highlighting the need for further validation in clinical settings.