Version 1
: Received: 21 May 2024 / Approved: 23 May 2024 / Online: 23 May 2024 (07:34:57 CEST)
How to cite:
MAHAJAN, A.; Badhe, D. P.; Mali, P. Integrating Network Pharmacology and Experimental Evaluation of Ocimum tenuiflorum (Tulsi) compounds targeting Breast Cancer Markers. Preprints2024, 2024051511. https://doi.org/10.20944/preprints202405.1511.v1
MAHAJAN, A.; Badhe, D. P.; Mali, P. Integrating Network Pharmacology and Experimental Evaluation of Ocimum tenuiflorum (Tulsi) compounds targeting Breast Cancer Markers. Preprints 2024, 2024051511. https://doi.org/10.20944/preprints202405.1511.v1
MAHAJAN, A.; Badhe, D. P.; Mali, P. Integrating Network Pharmacology and Experimental Evaluation of Ocimum tenuiflorum (Tulsi) compounds targeting Breast Cancer Markers. Preprints2024, 2024051511. https://doi.org/10.20944/preprints202405.1511.v1
APA Style
MAHAJAN, A., Badhe, D. P., & Mali, P. (2024). Integrating Network Pharmacology and Experimental Evaluation of <em>Ocimum tenuiflorum</em> (Tulsi) compounds targeting Breast Cancer Markers. Preprints. https://doi.org/10.20944/preprints202405.1511.v1
Chicago/Turabian Style
MAHAJAN, A., Dr. Pravin Badhe and Prashant Mali. 2024 "Integrating Network Pharmacology and Experimental Evaluation of <em>Ocimum tenuiflorum</em> (Tulsi) compounds targeting Breast Cancer Markers" Preprints. https://doi.org/10.20944/preprints202405.1511.v1
Abstract
One of the most prevalent and deadly types of cancer is breast cancer. The value and effectiveness of the current pharmacological therapy are, however, constrained. Using computational methods and publicly available data, the current study set out to identify the genes and molecular pathways linked to breast cancer. It also looked into potential treatments for the disease that would target these molecular processes. In this study, we mined genes that were strongly associated with breast cancer using text mining and GeneCodis. Using STRING and Cytoscape, protein-protein interaction (PPI) study was carried out. Candidate medications were then derived based on the drug-gene interaction study of the final genes. 2,658 genes linked to breast cancer were found by our investigation using text mining searches. Out of which 166 genes have been taken which are relevant to breast cancer. Ten genes representing ten pathways—which a total of ten proteins could target—were found by gene enrichment analysis. We have taken Holy Basil as our lead as it contains various bioactive compounds such as flavonoids, terpenoids, and phenolics, which have shown antioxidant, anti-inflammatory, and anticancer properties. For this analysis we choose the molecular docking technique to check the effects of different chemical constituents of Holy Tulsi on breast cancer targeted protein and compare their results. We’ve performed the molecular docking in between chemical constituents of Holy Basil and the targeted proteins and determined the binding affinity with the help of PyRx and BIOVIA Discovery studio software. Anti-mitotic activity of Pisum sativum using tulsi extract to check the cytotoxicity effect was done. To determine the toxicity level of the extract on rat liver was performed in the end. In conclusion, investigating candidate medications that target the genes/pathways relevant to breast cancer in order to uncover possible treatments may be accomplished through drug discovery employing in silico text mining and pathway analysis technologies along with the wet lab experimentation with plants and preclinicals.
Keywords
Breast cancer; network pharmacology; text mining; drug therapy; genes; pathway analysis; biological process; protein-protein interaction; degree and betweenness; molecular docking; meristematic cells; anti-mitotic; hepatotoxicity
Subject
Biology and Life Sciences, Cell and Developmental Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
