Creating Public MS/MS Libraries in NIST Format

Significance of the topic

The creation and curation of public MS/MS spectral libraries in NIST format is crucial for routine and advanced mass spectrometry (MS) workflows, including metabolomics, environmental analysis, forensic screening and pharmaceutical research. Well-constructed libraries enable reliable spectrum matching, structure-based searching, and improved confidence in identifications. Converting open-source libraries (MoNA, MS-DIAL, Enveda-180 and others) into NIST user libraries allows laboratories to integrate large experimental datasets into established NIST search tools and take advantage of advanced features such as hybrid searches and structure-aware lookups.

Study aims and overview

This handout/video documents practical steps and considerations for converting public LC-MS/MS libraries into NIST format. It (1) describes existing public collections (MoNA, MS-DIAL), (2) highlights recent changes to those collections (notably the July 2026 merge that added Enveda-180 to MoNA), (3) outlines the conversion workflow using Lib2NIST and related utilities, and (4) provides best practices for handling very large SDF/MSP datasets and for validating the resulting NIST libraries. The material is presented as a how-to reference for analysts who want to build tailored, searchable NIST-format libraries for local use.

Methods and workflow

The general conversion workflow demonstrated is as follows:

• Download the source archive from the public repository (e.g., MoNA LC-MS/MS SDF archive or MS-DIAL exports).
• Unzip and inspect the SDF (contains spectra and, when available, structures) or MSP files (spectra only).
• Use Lib2NIST (latest Windows build) to convert SDF/MSP to a NIST-format library and place the output in the NIST Mssearch folder (for example C:/NIST26/Mssearch).
• After conversion, run the NIST software action Tools → Rebuild Structure Search Database to index structural information so structure-based searches operate correctly.
• Perform validation searches with multiple search modes to verify library integrity.

Key practical notes:

• Large combined datasets (e.g., the post-2026 MoNA that includes Enveda-180) may produce SDF files multiple gigabytes in size and are impractical to open in typical Windows editors.
• Streaming techniques (PowerShell scripts) can filter records (for example to remove Enveda-180 entries) without loading the entire file into memory.
• Lib2NIST should always be the most recent version compatible with your NIST release (NIST26 or equivalent).
• Conversion from SDF may produce structural records that require database rebuilds to enable structure searches; if this step is skipped, structures appear but structure search fails.

Used instrumentation

Instrumentation referenced in the source material and relevant to the libraries:

• timsTOF Pro 2 (used to generate the Enveda-180 experimental spectra; raw Bruker .d files were part of the deposited dataset).
• Orbitrap-class LC-MS/MS instruments (MoNA LC-MS/MS Orbitrap subset used in the demonstration; ~159,463 spectra).
• General note on raw file formats: Bruker .d folders were explicitly mentioned in the Enveda data deposition, confirming these were instrument-generated raw data.

Key results and discussion

Practical outcomes and observations from the conversion exercise:

• Public conversion: The author has made two NIST-format library distributions publicly available (MoNA and MS-DIAL variants), together exceeding ~500,000 spectra and representing more than 150,000 structures.
• Enveda-180 impact: The addition of Enveda-180 to MoNA dramatically increased dataset size (Enveda-180 alone contains roughly 1.16 million spectra for ~184,330 unique drug-like compounds), creating practical storage and performance challenges for conversion and searching.
• Content suitability: Enveda-180 is experimentally derived and valuable for structural coverage, but its emphasis on Enamine REAL-space drug-like molecules may limit relevance for routine environmental, metabolomics, or forensic screening; many users may prefer to exclude these entries from their routine libraries.
• Technical challenges: Very large SDF files (2.4–2.7 GB) cannot be opened in standard Windows editors; streaming via PowerShell or programmatic filtering is recommended to create curated subsets before conversion. Adding a very large number of spectra can slow indexing and searching.
• Conversion caveats: MS-DIAL exports can be converted but may lack associated structures; SDF conversions must be followed by a structure database rebuild within NIST to enable structure searches. During the conversion process some interactive dialogs (e.g., repeated confirmation prompts) may require automation or scripting to proceed at scale.

Benefits and practical applications

Advantages of generating tailored NIST-format libraries:

• Custom content: Users can create libraries focused on their sample types (environmental extracts, human plasma, forensic matrices), improving search relevance and reducing false positives from irrelevant drug-like entries.
• Integration with NIST tools: Converting to NIST format allows use of advanced NIST search modes (identity MS/MS with precursor, high-resolution no-precursor, EI-normal, MS/MS hybrid, structure search), yielding more flexible identification strategies.
• Reproducibility and provenance: Local NIST libraries constructed from public sources can be documented and versioned, aiding QC and regulatory compliance.
• Performance trade-offs: Smaller, curated libraries can offer faster searches and easier maintenance than enormous, all-inclusive datasets.

Future trends and potential applications

Expected and recommended developments for MS/MS library creation and use:

• Integrated deconvolution + library searching: NIST26 and similar platforms are moving toward integrated deconvolution workflows to better handle pooled or coeluting spectra, improving spectral assignment quality.
• Automated curation and subsetting: Tools that programmatically filter large public datasets by chemical class, polarity, adduct, or experimental metadata will become standard to produce application-specific libraries.
• Cloud-based indexing and distributed search: To handle million-spectrum libraries without local performance penalties, cloud indexing and remote search services will gain traction.
• Community standards and metadata: Improved metadata annotation (collision energy, adduct, retention time, ion mobility/CCS) will enhance cross-laboratory utility of public spectra and support smarter automated matching.
• Hybrid search and structural prediction synergy: Combining experimental libraries with structure-prediction tools (SIRIUS-style formula annotation) and hybrid-spectrum search approaches will expand identification coverage while retaining experimental fidelity.

Conclusion

Converting public MS/MS collections to NIST format is a practical way to leverage large experimental datasets within widely used search tools, but it requires careful planning: selecting relevant content, handling very large files via streaming or programmatic filtering, using up-to-date conversion tools (Lib2NIST), rebuilding the structure search database, and validating multiple search modes. For many users, creating focused sub-libraries that exclude large drug-like collections such as Enveda-180 will yield better performance and more relevant identifications. Ongoing trends toward integrated deconvolution, automated curation, and cloud-enabled search will further simplify use of large public spectral resources.

References

James Little. Creating Public MS/MS Libraries in NIST Format: Video and Handout. Mass Spec Interpretation Services, 21 August 2026.

MoNA (MassBank of North America) LC-MS/MS spectral collection (public repository). 2026.

MS-DIAL LC-MS/MS public export datasets. 2026.

Enveda-180 experimental LC-MS/MS library (dataset derived from Enamine REAL-space compounds). MassIVE deposition MSV000102122. 2026.

Lib2NIST conversion utility (Windows). Latest release referenced for NIST26 integration. 2026.

NIST26 course and integrated deconvolution/library searching materials. 2026.