Versa DB:通过按需数据库协助 13C NMR 和 MS/MS 联合数据注释

IF 6.1 Q1 CHEMISTRY, MULTIDISCIPLINARY
Julien Cordonnier, Dr. Simon Remy, Prof. Dr. Jean-Hugues Renault, Dr. Jean-Marc Nuzillard
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引用次数: 0

摘要

通过 NMR 和 MS 在复杂混合物中进行化合物鉴定的最佳方法是挖掘实验数据库(DB)。实验数据库在完整性、可用性或数据质量方面经常出现局限性,因此预测数据库的使用越来越普遍。查询大型数据库可能会导致选择不可能的候选结构。因此,可以采用两种方法来消除重复:在搜索前对大型数据库进行过滤,或在大规模搜索后对结果进行评分。本研究采用的是前一种方法。据我们所知,nmrshiftdb2 是唯一可以在批处理模式下自由操作的开源 13NMR 化学位移预测器。CFM-ID 4.0 是性能最好的 ESI-MS/MS 图谱预测开源工具之一。LOTUS 是一个可自由使用的综合性二级代谢物数据库。由于数据编码和处理程序的多样性,将 LOTUS、CFM-ID 和 nmrshiftdb2 等开源数据库和软件集成到去复制工作流程中需要目前的编程技能。据我们所知,将化学结构收集、光谱数据预测和数据库建设无缝整合在一起的图形用户界面尚不存在。本研究提出了一种独立的软件工具,以简单的方式协助识别混合物成分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Versa DB: Assisting 13C NMR and MS/MS Joint Data Annotation Through On-Demand Databases

Versa DB: Assisting 13C NMR and MS/MS Joint Data Annotation Through On-Demand Databases

Compound identification in complex mixtures by NMR and MS is best achieved through experimental databases (DB) mining. Experimental DB frequently show limitations regarding their completeness, availability or data quality, thus making predicted database of increasing common use. Querying large databases may lead to select unlikely structure candidates. Two approaches to dereplication are thus possible: filtering of a large DB before search or scoring of the results after a large scale search. The present work relies on the former approach. As far as we know, nmrshiftdb2 is the only open-source 13NMR chemical shift predictor that can be freely operated in batch mode. CFM-ID 4.0 is one of the best-performing open-source tools for ESI-MS/MS spectra prediction. LOTUS is a freely usable and comprehensive collection of secondary metabolites. Integrating the open source database and software LOTUS, CFM-ID, and nmrshiftdb2 in a dereplication workflow requires presently programming skills, owing to the diversity of data encoding and processing procedures. A graphical user interface that integrates seamlessly chemical structure collection, spectral data prediction and database building still does not exist, as far as we know. The present work proposes a stand–alone software tool that assists the identification of mixture components in a simple way.

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