The Potential Compounds in Lansium parasiticum Leaf Extract for Breast Cancer Therapy: Metabolite Profiling, Pharmacological Network Analysis and In Silico Validation

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Abstract

Objective: This study aims to identify the compounds found in Lansium parasiticum leaf extract (LPLE) and explain its activity in the context of breast cancer prevention and therapy using a pharmacological network approach and its validation in silico to understand the molecular mechanisms involved. Methods: Identification of compounds in LPLE is done using Liquid Chromatography Tandem Mass Spectrophotometry (LC-MS/MS). We also identified absorption and bioavailability profiles using ADMET software. Predictions about the molecular mechanisms of the anti-cancer compounds of LPLE were made through a network pharmacological approach involving devices such as Cytoscape 3.9.1, GeneCards, Disgenet, STRING 2.0.0, the Kyoto Encyclopedia of Genes and Genomes (KEGG) path, and SRplot. Interactions between potential compounds with TP53 receptors were analyzed using site-specific molecular docking, using PyRx Autodock Vina 9.0 and Biovia Discovery Studio. Result: A total of 24 active compounds were successfully identified through LC-MS/MS. The results of the pharmacological network analysis of these compounds showed that there are four substances that have potential against the potential target gene of breast cancer, namely dihydrotestosterone with 8 target genes, Oxoberberine with 8 targets, Pregnenolone with 1 target gene, and Quercetine with 16 targets. The results of in silico validation revealed that the four compounds showed strong affinity to TP53, even higher than their original ligaments. Conclusion: The study successfully identified the active compounds in Lansium parasiticum leaf extract (LPLE) that have potential in the prevention and treatment of breast cancer.

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Mutiah, R., Safina, N. A. N., Janaloka, N. A., Zahira, S. R., Annisa, R., Febriyanti, A. P., & Maimunah, S. (2024). The Potential Compounds in Lansium parasiticum Leaf Extract for Breast Cancer Therapy: Metabolite Profiling, Pharmacological Network Analysis and In Silico Validation. Asian Pacific Journal of Cancer Prevention, 25(11), 3831–3840. https://doi.org/10.31557/APJCP.2024.25.11.3831

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