Artificial intelligence in natural products research

Xiao Yuan; Xiaobo Yang; Qiyuan Pan; Cheng Luo; Xin Luan; Hao Zhang

doi:10.1016/S1875-5364(25)60902-2

Chinese Journal of Natural Medicines ›› 2025, Vol. 23 ›› Issue (11) :1310 -1328. DOI: 10.1016/S1875-5364(25)60902-2

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Artificial intelligence in natural products research

Xiao Yuan ¹^,^∆
, Xiaobo Yang ²^,^∆
, Qiyuan Pan ¹
, Cheng Luo ²^,³^,⁴
, Xin Luan ¹^,^*
, Hao Zhang ¹^,^*

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Abstract

Artificial intelligence (AI) has emerged as a transformative technology in accelerating drug discovery and development within natural medicines research. Natural medicines, characterized by their complex chemical compositions and multifaceted pharmacological mechanisms, demonstrate widespread application in treating diverse diseases. However, research and development face significant challenges, including component complexity, extraction difficulties, and efficacy validation. AI technology, particularly through deep learning (DL) and machine learning (ML) approaches, enables efficient analysis of extensive datasets, facilitating drug screening, component analysis, and pharmacological mechanism elucidation. The implementation of AI technology demonstrates considerable potential in virtual screening, compound optimization, and synthetic pathway design, thereby enhancing natural medicines’ bioavailability and safety profiles. Nevertheless, current applications encounter limitations regarding data quality, model interpretability, and ethical considerations. As AI technologies continue to evolve, natural medicines research and development will achieve greater efficiency and precision, advancing both personalized medicine and contemporary drug development approaches.

Keywords

Natural products / Artificial intelligence / Deep learning / Drug discovery / Model interpretability

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Xiao Yuan, Xiaobo Yang, Qiyuan Pan, Cheng Luo, Xin Luan, Hao Zhang. Artificial intelligence in natural products research. Chinese Journal of Natural Medicines, 2025, 23(11): 1310-1328 DOI:10.1016/S1875-5364(25)60902-2

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