基于结构的RiPP识别元素的发现和定义
Miriam H Bregman1, Dillon P Cogan2, Kyle E Shelton1
1Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
mSystems
|November 18, 2025
概括
这项研究通过将基于结构的搜索与AlphaFold预测相结合来增强RiPP发现,识别了9万多个RiPP识别元素 (RRE) 和13个识别动机. 这提高了基因组挖掘的准确性,并扩大了对隐藏的RiPP生物合成途径的访问.
科学领域:
- 自然产品的发现自然产品的发现.
- 生物信息学是一种生物信息学.
- 结构生物学是结构生物学.
- 基因组学就是基因组学.
背景情况:
- 核糖体合成和翻译后改性 (RiPPs) 是各种自然产物,在各种生物过程中至关重要.
- RiPP识别元素 (RRE) 是RiPP生物合成和基因组挖掘所必需的关键结域.
- 现有的RRE-Finder工具面临的局限性是由于高假阳性率和难以识别序列分离的RRE.
研究的目的:
- 通过加强RRE识别来提高RiPP基因组挖掘的准确性和范围.
- 利用基于结构的搜索 (Foldseek) 和AlphaFold预测来发现序列分离的RRE及其相关的前体.
- 完善生物信息工具,以便更全面地识别依赖RRE的生物合成途径.
主要方法:
- Employed Foldseek用于对AlphaFold数据库进行基于结构的搜索,以识别不同的RRE.
- 开发了11个新的Foldseek衍生的隐藏马尔科夫模型 (HMM),并为RRE-Finder改进了现有的模型.
- 利用AlphaFold 3来预测RRE-复合体,使识别序列的映射成为可能.
主要成果:
- 更新的工作流确定了超过9万个高可信度RRE,与原始模型相比,UniProt的检索率几乎翻了一番.
- 发现了新的RRE域融合和5000个以前未知的RRE域,保留了正规折叠,但提供了新的生物信息处理.
- 通过预测RRE-前体相互作用,在RiPP类中映射出13个不同的识别序列动图.
结论:
- 基于结构的搜索和高级建模的整合显著提高了RiPP基因组挖掘的准确性和效率.
- 这种改进的方法扩大了已知依赖RRE的生物合成途径的范围,提供了以前隐藏的自然产品.
- 这些发现简化了RiPP前体及其相关RRE的识别,促进了对RiPP多样性和功能的进一步研究.
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