In Silico Studies of Stylissa Carteri-Compounds against EGFR and RAF Proteins in Triple-Negative Breast Cancer
Triple-negative breast cancer (TNBC) represents a highly aggressive form of breast cancer, and the treatment options available are regarded as particularly challenging. The lack of specific molecular targets, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), accounts for this situation. This study investigates the molecular interactions between natural compounds derived from Stylissa carteri and Epidermal Growth Factor Receptor (EGFR) and RAF proteins, which are promising targets for therapeutic strategies in triple-negative breast cancer (TNBC), utilizing in silico techniques. Nine compounds derived from Stylissa carteri were obtained from the Knapsack and PubChem servers. These compounds' biological activities and interactions with EGFR and RAF proteins were analyzed. The findings indicated that the nine compounds exhibited various biological activities inhibiting TNBC. Docking and molecular dynamics analysis revealed that stevensine and dibutyl phthalate exhibited the highest binding affinity and the most stable interactions with the EGFR-RAF protein complex. Docking analysis revealed binding affinity values between −5.4 and −7.9 kcal/mol. The most robust binding interaction was noted for (Z)-hymenialdisine with RAF (−7.9 kcal/mol), whereas 1,2-benzenediol exhibited the weakest interaction (−5.7 kcal/mol). Dibutyl phthalate exhibited the highest binding affinity for EGFR, measured at −7.0 kcal/mol. The findings indicate that compounds derived from Stylissa carteri exhibit potential efficacy in targeting EGFR and RAF in triple-negative breast cancer (TNBC).
Authors
- Nafisah Nafisah
- Sári
- Ma’arif
- Krama
- Isfaeni
- Rusdi
- Gholam
Institutions
- State University of Semarang (ID)
- Universitas Negeri Surabaya (ID)
- Center for Plant Conservation (US)
- State University of Jakarta (ID)
- Institut Teknologi Nasional Malang (ID)
Publication Details
- Journal
- Tropical Journal of Natural Product Research
- Published
- 2025-07-01
- DOI
- https://doi.org/10.26538/tjnpr/v9i6.77
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00