使用整合序列和基于人工智能的结构方法对Mycobacteroides abscessus蛋白质的功能 (重新) 标注
Pranavathiyani Gnanasekar1, Simran Gambhir1, Priyadarshan Kinatukara2
1Bioinformatics Centre, CSIR-Institute of Microbial Technology (IMTECH), Sector 39A, Chandigarh, 160036, India.
Current research in structural biology
|September 2, 2025
概括
这项研究使用序列和人工智能驱动的基于结构的方法增强了Mycobacteroides (MAB) 蛋白质的功能注释. 新的和精细的注释被分配, 提高我们对这一关键的耐药病原体的理解.
科学领域:
- 蛋白质组学和生物信息学
- 微生物学与传染病
背景情况:
- 蛋白质的功能性注释对于理解生物体的生物学和病变是必不可少的,特别是对于像Mycobacteroides abscessus (MAB) 这样的机会性病原体.
- 一大部分MAB蛋白质组的注释很差,阻碍了对其功能格局,药物耐药性机制和传播潜力的理解.
- 对MAB蛋白质的功能描述和基因本体学 (GO) 术语进行改进至关重要,以确定潜在的药物标.
研究的目的:
- 使用序列和人工智能驱动的基于结构的方法系统地 (重新) 标注Mycobacteroides瘤蛋白质.
- 解决MAB蛋白,包括基本基因的功能注释的重大差距.
- 利用预测的蛋白质结构和序列相似性来改善功能性特征.
主要方法:
- 根据NR数据库进行基于序列的相似性搜索和基于HMM的功能域 (Pfam,CATH) 搜索.
- 使用AI预测MAB蛋白质的结构 (AlphaFold) 并执行基于结构的相似性搜索 (Foldseek) 来转移GO注释.
- 对于缺乏AlphaFold结构的蛋白质,采用综合序列和基于结构的方法.
主要成果:
- 为374种MAB蛋白赋予了新的GO注释,并对885种蛋白进行了改进,包括以前未注释的基本基因.
- 即使对于没有可用的AlphaFold结构的蛋白质,也成功地应用了基于序列和结构的组合注释策略.
- 鉴定了与Mycobacterium tuberculosis相同的MAB蛋白的残留水平差异,可能与耐药性有关.
结论:
- 这项研究证明了基于序列和人工智能结构的综合方法对大规模蛋白质组功能注释的有效性.
- 这种方法显著提高了对Mycobacteroides蛋白的功能理解,有助于研究病变和耐药性.
- 开发的方法广泛适用于其他感兴趣的生物的功能性蛋白质组注释.
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