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About this paper
Sharanya Manoharan, Balu Bhasuran, Oviya Ramalakshmi Iyyappan, Mohamed Saleem Abdul Shukkoor, Malathi Sellapan, Kalpana Raja
An integrated AI-driven framework systematically extracted and visualized complex relationships among microRNA (miRNA), messenger RNA (mRNA), disease, and drug entities, uncovering potential drug repurposing candidates for chronic diseases. The approach combined large language models for literature mining, a relation extraction tool, network analysis, and clinical data validation with MIMIC-IV, identifying key miRNA and drug hubs in disease-associated networks.
Key insights
- Specific miRNAs (e.g., miR-21, miR-155) act as central 'master regulators' by connecting multiple diseases, mRNAs, and drugs, highlighting their roles in diverse biological pathways.
- The integrated framework identified both known and potential novel drug repurposing candidates for chronic diseases by mechanistically linking drugs to diseases through miRNA and mRNA interactions.
- Network analysis revealed a highly interconnected 'small-world' structure with prominent hub nodes and shared molecular mechanisms, particularly indicating comorbidity connectivity with cancer.
Summary by alphaXiv.
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