Network pharmacology integrated molecular docking of fucoidan against oral cancer and in vitro evaluation- A study using GEO datasets

褐藻糖胶 小桶 毒理基因组学 计算生物学 药物发现 药理学 药物重新定位 生物信息学 药品 生物 基因 生物化学 转录组 基因表达 遗传学 多糖
作者
Arul Jayanthi Antonisamy,Karthikeyan Rajendran,Premnath Dhanaraj
出处
期刊:Journal of Biomolecular Structure & Dynamics [Taylor & Francis]
卷期号:43 (15): 8397-8420 被引量:3
标识
DOI:10.1080/07391102.2024.2316771
摘要

Oral cancer is a widespread health concern in rural India due to a lack of awareness, delayed diagnosis and limited access to affordable treatment options. The current chemotherapy has notable side effects, underscoring the need for new drug candidates with improved bioavailability and specificity. In this current research, fucoidan, a sulphated polysaccharide, was extracted from the brown algae Spatoglossum asperum, and shown to be cytotoxic in vitro against oral cancer cells (KB cell line) at an IC50 of 107.76 µg/ml, suggesting its potential as a drug candidate. This study further aimed to explore the potential therapeutic implications of fucoidan in managing oral cancer using network pharmacology. PharmMapper, Comparative Toxicogenomics Database and SuperPred were initially used to identify fucoidan protein targets. The identified targets were further screened against Gene Expression Omnibus (GSE23558, GSE25099 and GSE146483), OMIM, TCGA and GeneCards datasets to identify oral cancer-specific protein targets. The interactions between the selected proteins were visualised using STRING and Cytoscape. Subsequently, Database for Annotation, Visualization and Integrated Discovery was used for gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of candidate targets. The cancer-related network was assessed using CancerGeneNet, while life expectancy based on the expression of the top 10 CytoHubba ranked hub genes was evaluated using Kaplan-Meier plots. Finally, EGFR, AKT1, HSP90AA1 and SRC were selected for docking and molecular dynamics simulation with fucoidan, using Maestro and GROMACS, respectively.
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