自然与机器相遇:人工智能在天然产品中复兴 药物发现
Rajesh Muthuraj1, Jaikanth Chandrasekaran2
1Department of Pharmacology, Sri Ramachandra Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research (Deemed to Be University), Chennai, 600116, Tamil Nadu, India.
Natural products and bioprospecting
|March 2, 2026
概括
人工智能 (AI) 可以克服天然产品 (NP) 药物发现中的传统瓶. 通过整合人工智能工具,研究人员可以加速从自然衍生化合物中识别和开发新型治疗方法.
科学领域:
- 药物发现 药物发现 药物发现
- 自然产品 自然产品
- 人工智能的人工智能
背景情况:
- 自然产品 (NPs) 是药物发现的重要来源,但传统方法面临着低产量和可扩展性等挑战.
- 合成化学的兴起已经掩盖了NP的发现,尽管合成药物往往是以NP为灵感.
- 经典的NP工作流与复杂性,低收益率,重新发现和可扩展性作斗争.
研究的目的:
- 批判性地检查传统天然产品发现中的瓶.
- 概述如何将人工智能 (AI) 整合到NP发现管道中.
- 为协同AI-NP集成提供一个框架.
主要方法:
- 在NP发现中对AI应用的审查,包括NLP,机器学习和基因组挖掘.
- 分析人工智能在脱复制和化学信息学方面的进步.
- 检查抗生素,抗癌药物和传统医学的现代化案例研究.
主要成果:
- 人工智能为NP发现的长期挑战提供了解决方案,提高了效率和可扩展性.
- 人工智能集成加速了早期发现,并提高了翻译相关性.
- 像GNPS2这样的平台在AI驱动的NP研究中展示了可扩展的进展.
结论:
- 人工智能是NP研究的补充工具,而不是竞争工具,可以有效地探索化学多样性.
- 人工智能整合使传统医学现代化,并加速新疗法的发现.
- 新兴的人工智能范式,如量子机器学习和联合生态系统,有望进一步进步.
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