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Updated: Jun 26, 2025

Cellular Lipid Extraction for Targeted Stable Isotope Dilution Liquid Chromatography-Mass Spectrometry Analysis
Published on: November 17, 2011
InChI isotopologue and isotopomer specifications
Hunter N B Moseley1, Philippe Rocca-Serra2, Reza M Salek3
1Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY, USA. hunter.moseley@uky.edu.
This study proposes an extension to the International Chemical Identifier (InChI) standard for representing isotopically-resolved chemical entities. This innovation enhances data annotation for analytical chemistry, promoting FAIR data principles and Open Science.
Area of Science:
- Chemical informatics
- Analytical chemistry
- Data science
Background:
- The International Union of Pure and Applied Chemistry (IUPAC) International Chemical Identifier (InChI) is a standard for chemical structure representation.
- Current InChI limitations exist in fully representing isotopically-resolved chemical entities, especially with ambiguous isotope localization.
- Accurate chemical identification is crucial for analytical instrumentation like NMR and mass spectrometry.
Purpose of the Study:
- To propose an extension to the InChI standard for improved representation of isotopically-resolved chemical entities.
- To enhance the interpretation of the existing isotopic layer and introduce a new isotopologue layer.
- To support unique identification of chemical features detected in analytical measurements.
Main Methods:
- Development of an extended InChI standard specification.
- Incorporation of an improved isotopic layer interpretation.
- Introduction of a novel isotopologue layer for ambiguous isotope localization.
Main Results:
- A proposed extension to the InChI standard capable of representing isotopically-resolved chemical entities with varying ambiguity.
- Enhanced capability for unique identification of chemical features from analytical data.
- Improved support for annotating analytical datasets.
Conclusions:
- The proposed InChI extension facilitates better characterization of chemical entities in analytical data.
- This advancement supports the FAIR data principles (Findable, Accessible, Interoperable, Reusable) for chemical datasets.
- The extension promotes Open Science practices within the chemistry community.
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