AI-Guided Network Pharmacology and Docking-Based Exploration of the Synergistic Anticancer Effects of Peganum harmala and Bee Venom: An Integrative Phytotherapeutic Strategy

Abstract

Background:
Cancer continues to pose a significant global health challenge, highlighting the need for innovative treatment methods that go beyond traditional single-target medications. Natural substances like Peganum harmala and bee venom exhibit unique bioactive properties; however, their combined anticancer effects have yet to be investigated.

Objective:
This study aims to explore the synergistic anticancer mechanisms of Peganum harmala and bee venom utilizing network pharmacology and molecular docking techniques.

Methods:
The phytochemical compositions of both substances were analyzed through literature reviews and computational assessments. Protein targets were predicted using SwissTargetPrediction and STRING databases, followed by pathway enrichment analysis via KEGG and DAVID. Molecular docking was conducted with AutoDock Vina against significant cancer targets (Bcl-2, p53, PI3K, EGFR), with binding interactions visualized using PyMOL and Discovery Studio.

Results:
Harmine and melittin were identified as key bioactive compounds with strong binding affinities towards proteins associated with apoptosis. Network analysis uncovered shared targets such as TP53, CASP3, and BCL2, which are enriched in pathways related to apoptosis, PI3K-Akt, and MAPK. Docking simulations indicated stable interactions that support the potential for synergy.

Conclusion:
This research offers substantial computational evidence for the synergistic anticancer capabilities of Peganum harmala and bee venom. The multi-targeted mechanisms observed necessitate further validation in preclinical cancer models and underscore the potential of AI-assisted discovery of natural compounds.