Wiley Spectral Webinar Part V: Creating and Sharing User EI and MS/MS Libraries

Significance of the Topic

The ability to create and share custom electron ionization and tandem mass spectral libraries empowers analytical chemists to identify unknown compounds, streamline quality control workflows and support large corporate research networks. User-generated libraries supplement commercial databases with specific in-house standards, annotations and process-related spectra that improve confidence in feature identification and support rapid decision making.

Objectives and Overview

This work outlines a practical approach for building, curating and distributing user EI and MS/MS libraries using only NIST software tools and simple batch scripting. Key aims include:

• Describing the steps to import, edit and annotate spectra
• Defining user tags and comment fields for metadata
• Implementing quality checks and indexing routines
• Automating library merging and global distribution

Methodology and Instrumentation

User libraries are constructed within NIST MS Search, AMDIS and MS Interpreter environments under Windows. A typical workflow comprises:

• Importing processed GC-EI or LC-MS/MS spectra into the SpecList window
• Drawing structures in chemical drawing software and pasting into the spectrum record
• Editing peak lists, calculating exact mass, formula and adding retention index
• Defining custom tags (eg analyst, notebook number) to appear as separate metadata lines
• Performing quality checks such as InChIKey exact‐structure searches, hybrid and interpreter diagnostics
• Indexing libraries for identity, structure, hybrid and InChIKey searches via Lib2NIST utilities
• Automating daily merges and updates across a network using simple DOS batch scripts triggered by Windows scheduler

Key Results and Discussion

At Eastman Chemical Company, over 50 networked GC-MS and LC-MS/MS instruments contribute to a corporate user library containing approximately 60 000 EI and 3 000 MS/MS spectra. Entries range from high-confidence standards to annotated unknowns marked with question flags. The tagging system and comment fields enable rapid retrieval of process-related or commercial components, supporting spill source tracing, process troubleshooting and environmental monitoring. The automated merge and distribution approach ensures that new entries are available to all users worldwide within 24 hours.

Benefits and Practical Applications

The described method requires no additional hardware or expensive licenses beyond NIST software. Benefits include:

• High flexibility to capture proprietary and in-process compounds
• Improved unknown identification accuracy through custom metadata
• Reduced turnaround time for library updates across global sites
• Enhanced traceability of spectra back to analytical notebooks and operators

Future Trends and Potential Applications

Advances may include cloud-based library hosting, integration with machine learning-driven spectral prediction, incorporation of accurate mass MS/MS fragmentation modeling and direct interfacing with large language models for automated annotation. Expanded hybrid and similarity search algorithms will further improve identification of novel or modified compounds in metabolomics, pharmaceuticals and environmental analysis.

Conclusion

Building and sharing user-generated EI and MS/MS libraries using NIST tools and simple scripting offers a cost-effective, scalable solution for corporate and research laboratories. The approach enhances identification workflows, preserves institutional knowledge and supports rapid dissemination of critical spectral data.

References

1. James Little Mass Spectral Resource Website
2. NIST Search Software Detailed Manual
3. AMDIS Program for Data Processing Detailed Manual
4. Basic Instructions for Using AMDIS with NIST Search
5. Nightly Automatic Update of Users’ Libraries
6. Using NIST Search from Instrument Manufacturers’ Software
7. Chemical Ionization for MW Determination
8. Trimethylsilyl Derivatives for GC-MS
9. Methyl Ester Derivatives for GC-MS
10. SciFinder/ChemSpider and Accurate Mass LC-MS Data for Unknown IDs
11. Surfactant Identification
12. QuickGuide for Retention Indices with AMDIS
13. Modeling Ion Fragmentation by MS Interpreter Software
14. Enhancements to NIST MS Interpreter for High Mass Accuracy MS/MS
15. Automated Method for Verifying Structure-Spectral Consistency
16. Hybrid Search Algorithm for Illicit Drug Identification
17. Hybrid Search in Proteomics
18. Hybrid Search for Metabolite Identification
19. Structure Annotation in Untargeted Metabolomics
20. Current Handouts for Webinar Series, Parts I–V
21. Lipid Matrix Ionization Effects in LC-MS
22. Mass Spectral Similarity Mapping in Hybrid Searches
23. User Manual for Wiley Libraries