计算科学技术为获取天然产物的隐藏化学多样性提供了新手段，开拓了药物发现的新可能。机器学习等人工智能方法促进了计算药物设计，有助于预测生物活性和针对特定靶点进行新药设计。文章讨论了当前和未来如何发挥这些技术协同效应的优势，从海量天然产物中有效识别药物候选compound。
介绍了各种人工智能方法在基因组学、代谢组学和表型数据挖掘、生物活性预测、靶点识别等方面的应用。讨论了构建高质量数据集、算法验证等关键挑战。
多位作者从化学信息学、药物设计、代谢组学等视角对该领域进行了全面综述。 文章系统阐述了人工智能为药物发现提供的新视角和可能。
《Artificial intelligence for natural product drug discovery | Nature Reviews Drug Discovery》
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