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Advancing TCM-derived active natural product drug discovery for novel drug targets: Insights from AI powered tools

Year: 2026

Type: article

Abstract: The discovery of natural products targeting novel and underexplored biological targets is deemed essential, as it underpins the advancement of innovative therapeutics across a broad spectrum of diseases. With the rapid advancement of artificial intelligence (AI) and the application of diverse drug discovery strategies, including multi-omics integration, network target prediction, virtual screening, and drug-target interaction prediction, these strategies are profoundly shaping the field, and active natural product-based drug discovery from traditional Chinese medicine has entered a new phase. In this era, multimodal and high-dimensional data can be integrated within the context of big data to enhance both its theoretical foundations and technical capabilities. Despite these advancements, AI-driven natural product drug discovery still confronts substantial challenges, particularly those associated with ensuring data and research quality, as well as achieving more profound scientific discoveries. To obtain more precise and biomedically meaningful results, further innovations in this field are therefore required. In essence, integrating high-dimensional data, network modeling, and intelligent screening within a closed-loop validation framework empowers AI and big data paradigms to catalyze the precise discovery of bioactive constituents, thereby unlocking new frontiers in target-directed therapeutics for complex diseases.

Source: Chinese Herbal Medicines

DOI: 10.1016/j.chmed.2026.07.007