1. AI-driven drug discovery from natural products
- Author
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Feng-Lei Duan, Chun-Bao Duan, Hui-Lin Xu, Xin-Ying Zhao, Otgonpurev Sukhbaatar, Jie Gao, Ming-Zhi Zhang, Wei-Hua Zhang, and Yu-Cheng Gu
- Subjects
Natural product drug discovery ,Deeping study ,Predicting targets ,Biological activity ,Molecular featurization ,Agriculture (General) ,S1-972 ,Biochemistry ,QD415-436 ,Chemistry ,QD1-999 - Abstract
The latest review published in Nature Reviews Drug Discovery by Michael W. Mullowney and co-authors focuses on the use of artificial intelligence techniques, specifically machine learning, in natural product drug discovery. The authors discussed various applications of AI in this field, such as genome and metabolome mining, structural characterization of natural products, and predicting targets and biological activities of these compounds. They also highlighted the challenges associated with creating and managing large datasets for training algorithms, as well as strategies to address these obstacles. Additionally, the authors examine common pitfalls in algorithm training and offer suggestions for avoiding them.
- Published
- 2024
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