READRetro:自然产品生物合成预测与检索增强的双视图逆合成
Taein Kim1, Seul Lee2, Yejin Kwak3
1Department of Biological Sciences, KAIST, Daejeon, 34141, Korea.
The New phytologist
|July 31, 2024
概括
我们开发了READRetro,这是一个用于预测植物天然产品生物合成途径的新工具. 这种方法改善了复杂代谢途径的预测,有助于发现植物二次代谢产物.
科学领域:
- 植物生物化学和新陈代谢学
- 生物信息学和计算生物学
- 自然产品的发现自然产品的发现.
背景情况:
- 植物产生各种不同的二次代谢物,对生态相互作用至关重要,具有显著的生物活性.
- 预测这些植物天然产品从点分子到代谢前体的完整生物合成途径是一个相当大的挑战.
- 现有的生物逆合成模型经常与这些途径的复杂性作斗争.
研究的目的:
- 介绍READRetro (检索增强双视 retrosynthesis),一个新的生物回归合成工具,旨在预测植物天然产品生物合成途径.
- 克服传统模型在预测复杂代谢途径方面的局限性.
- 为研究植物二次代谢物生物合成的研究人员提供实用解决方案.
主要方法:
- READRetro集成了先进的深度学习架构,集体方法和双重检索器,用于增强路径预测.
- 该模型在单步和多步逆合成任务中进行了评估.
- 性能由其预测已知路径和提出新路径的能力来评估.
主要成果:
- READRetro的每个组件都在预测生物合成途径方面显著改善.
- 该工具成功地预测了已知的二次代谢物的途径,例如单二醇类化合物.
- READRetro还提出了一种以前未知的天然产品menisdaurilide的途径.
结论:
- READRetro为植物天然产品的生物逆合成提供了一个实用和有效的解决方案.
- 该工具处理复杂路径和预测新路径的能力突出了其在自然产品研究中的实用性.
- 一个用户友好的网站和开源代码可用于促进植物二次代谢物生物合成和生产的研究.
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