人工智能和机械建模用于描述自然产品的生物合成途径
Byung Tae Lee1, Byeongsub Lee2, Joon Young Kwon1
1Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea. ehukim@kaist.ac.kr.
Natural product reports
|November 7, 2025
概括
包括人工智能 (AI) 和机械模型在内的计算方法正在彻底改变对自然产品生物合成的研究. 这些方法加速了有价值的生物活性化合物的发现和工程.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 自然产品 化学 化学
背景情况:
- 自然产品是生物活性化合物的重要来源.
- 由于复杂的基因型-表型联系,阐明生物合成途径具有挑战性.
- 在这个领域,计算方法越来越重要.
研究的目的:
- 审查自然产品生物合成的计算方法.
- 在路径阐明中强调AI和机械模型.
- 讨论自然产品发现的未来机会.
主要方法:
- 检查用于计算研究的关键数据库.
- 对人工智能驱动的途径和酶基质预测方法的审查.
- 对机械模拟进行分析,以获得能量和结构洞察力.
主要成果:
- 人工智能和机械模型为路径预测提供了强大的工具.
- 数据库对于支持计算自然产品研究至关重要.
- 整合策略可以加速发现和应用.
结论:
- 计算方法正在改变自然产品生物合成研究.
- 未来的工作应该专注于整合人工智能,建模和数据库.
- 这些进展将推动药物发现和生物技术方面的创新.
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