PyINETA:在NMR代谢学中集成INADEQUATE-JRES的开源平台
Rahil Taujale1,2, Mario Uchimiya2, Chaevien S Clendinen3
1Institute of Bioinformatics, University of Georgia, 120 E Green St, Athens, GA, USA.
bioRxiv : the preprint server for biology
|July 19, 2024
概括
PyINETA是一个新的Python代谢学工具,可以分析不充分的NMR数据. 它整合了多个NMR实验,使得可靠的化合物注释成为可能,并揭示了组织中的代谢途径.
科学领域:
- 代谢学 代谢学 代谢学
- 结构化解化 结构化解化
- 核磁共振 (NMR) 光谱学 核磁共振 (NMR) 光谱学
背景情况:
- 高可信度化合物注释在代谢学中至关重要.
- 不足够的 (令人难以置信的自然丰富的双量子转移实验) NMR实验对于结构阐明是强大的,但在代谢学中未得到充分利用.
- 现有的平台缺乏社区对不充分的数据和与其他NMR实验的整合的支持.
研究的目的:
- 介绍PyINETA,这是一个开源的Python平台,用于INADEQUATE网络分析.
- 从INADEQUATE实验提供自动化结构信息,并将其与补充的NMR数据集成,例如13C J-resolved (13C-JRES) 实验.
- 为了提高代谢学化合物注释的透明度和可复制性.
主要方法:
- 开发PyINETA,一个基于Python的管道,用于不充分的网络分析.
- 将INADEQUATE数据与13C-JRES实验输出的整合.
- 自动化数据库搜索和信息集成.
- 为了透明度,对管道参数和输出进行跟踪.
主要成果:
- 在一项小鼠模型研究中,PyINETA成功地整合了INADEQUATE和13C-JRES数据.
- 这项研究揭示了13C标记氨基酸在各种器官 (肝脏,脏,胰腺,肌肉,肺) 的组织特异分布和转化.
- PyINETA提供了有价值的碎片信息,用于识别未知的化合物.
结论:
- PyINETA提供了一个强大的,自动化解决方案,用于将INADEQUATE和其他NMR数据集成到代谢学中.
- 该平台促进了自信的化合物注释和代谢途径的阐明.
- PyINETA增强了INADEQUATE实验在代谢学研究中的实用性,并可在NMRbox.
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