Multi-Omics Network Analysis for Mechanism-Based Discovery of Natural Product Therapeutics
Keywords:
multi-omics integration; network medicine; natural product therapeutics; mechanism-based discovery; systems pharmacology; data governance; biomedical infrastructureAbstract
The integration of multi-omics data with network-based analytical frameworks has become a central strategy for understanding the mechanisms of action of natural product therapeutics. Natural products frequently exhibit polypharmacological behavior that cannot be adequately captured by single-target models. Multi-omics network analysis provides a systems-level representation in which genomic, transcriptomic, proteomic, metabolomic, and phenotypic layers are jointly modeled to reveal how natural product interventions perturb molecular interaction networks and disease modules. This paper presents a systemic examination of the conceptual foundations, integration architectures, network construction methods, and mechanism-based discovery workflows that support the study of natural products. It addresses structural trade-offs among data integration paradigms, the interpretive challenges of network community detection, and the importance of robustness and fairness in computational predictions. The discussion extends beyond algorithmic performance to consider data governance, reproducibility, sustainability, deployment infrastructure, and policy implications. The analysis emphasizes that mechanism-based discovery of natural product therapeutics is not solely a technical problem but a socio-technical challenge requiring coherent institutional coordination, transparent validation standards, and equitable data-sharing practices. The paper situates multi-omics network analysis within broader efforts to modernize natural product pharmacology while preserving the complexity and contextual richness of traditional therapeutic knowledge. It concludes by outlining forward-looking perspectives on federated data ecosystems, explainable network models, and regulatory frameworks that can support sustainable translation of natural product candidates into clinically relevant interventions.
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