Proposed Confidence Scale and ID Score in the Identification of Known-Unknown Compounds Using High Resolution MS Data

Area of Science:

• Analytical Chemistry
• Metabolomics
• Forensic Science

Background:

• High-resolution mass spectrometry (HRMS) enables untargeted acquisition, revealing unexpected compounds.
• Accurate identification of these compounds is crucial for interpretation, but reference standards are often unavailable.
• Existing methods lack a standardized approach to evaluate confidence in putative identifications.

Purpose of the Study:

• To propose a novel confidence scale and scoring system for identifying known-unknown compounds using (LC-)HRMS data.
• To bridge the gap between metabolomics and screening laboratory communities.
• To provide a method for evaluating the reliability of putative identifications before targeted analysis.

Main Methods:

• Developed a confidence scale based on European Commission (2007/657/EC) and Metabolomics Standard Initiative (MSI) guidelines.
• Defined an identification (ID) score [number, letter, number] based on three criteria: General Identification Category, Chromatography Class, and Identification Point Level.
• Applied the scale to (LC-) HRMS data for non-peptidic compounds with database entries.

Main Results:

• The proposed scale and score provide a structured approach to assess the confidence of putative compound identifications.
• The ID score (e.g., 2D3) quantifies identification reliability based on available data.
• Demonstrated the utility of the scoring system with three examples of known-unknown compound identifications.

Conclusions:

• The developed confidence scale and ID score enhance the reliability of compound identification from HRMS data, especially when reference standards are absent.
• This system facilitates more confident preliminary diagnoses and guides subsequent targeted analyses.
• It offers a standardized framework for evaluating putative identifications in diverse analytical fields.