Unknown Identification Using KnowItAll Adaptive MS and IR Search “Real World Example”

Importance of the Topic

The reliable identification of unknown compounds is a cornerstone of analytical chemistry, impacting fields such as forensic science, pharmaceutical development and industrial quality control. Combining multiple spectroscopic and spectrometric techniques enhances confidence in structural assignments and enables the detection of novel or illicit substances not present in standard libraries.

Objectives and Study Overview

This study demonstrates the application of a vendor-neutral, integrated software solution (KnowItAll™) for the adaptive identification of an unknown white powder. Key aims included comparing standard mass spectral library searching with an adaptive hybrid MS search, supplementing results with infrared (IR) mixture analysis and confirming a tentative structure for a fentanyl-related species.

Methodology and Instrumentation

• Software Platform: KnowItAll™ with integrated modules for IR, Raman, MS, NMR and UV across >170 file formats
• Reference Libraries: ~2.5 million spectra (IR 264 K, Raman 25 K, EI MS 1.25 M, NMR 894 K, UV 30 K)
• Adaptive MS Search: Patented algorithm aligning peaks shifted by Δm (nominal mass difference) and calculating a hybrid Hit Quality Index (HQI)
• IR Mixture Analysis: “Mixture 2” search option to deconvolute overlapping bands
• Instrumentation: GC-MS for EI spectra, FT-IR for mid-infrared analysis

Main Results and Discussion

Standard identity search of the EI mass spectrum failed to retrieve meaningful hits (HQI <70). The adaptive MS search identified top candidates with HQI >70 by accounting for mass shifts corresponding to the addition or loss of fragments (e.g., Δm=16 for oxygen insertion). The three highest-ranking adaptive hits suggested structural analogues with plausible fragment modifications.

IR analysis revealed a broad band from 2300–2900 cm⁻¹, indicative of a mixture. Applying the “Mixture 2” search yielded a combination of a carbamate and a hydrochloride salt, consistent with the MS-based fentanyl analogue hypothesis. Comparison of individual component spectra confirmed the presence of carbonyl and ammonium salt features.

Benefits and Practical Applications

• Extended Library Coverage: Adaptive search uncovers analogues not present in standard libraries, broadening dynamic range for unknown identification
• Multi-Spectral Correlation: Integration of MS and IR mixture analysis enhances structural confidence
• User Library Creation: Custom spectra can be added to support specialized workflows in forensic and pharmaceutical laboratories

Future Trends and Applications

• Expansion to High-Resolution MS: Incorporating accurate mass data for finer Δm discrimination
• Machine Learning Integration: Automating pattern recognition across multi-spectral data sets
• Real-Time Screening: Deployment in portable instruments for on-site forensic and environmental monitoring
• Enhanced Mixture Deconvolution: Advanced algorithms for complex formulations and biological matrices

Conclusion

The adaptive hybrid search within KnowItAll™ successfully identified a fentanyl-related hydrochloride salt from an unknown white powder, overcoming limitations of traditional library matching. Coupled IR mixture analysis confirmed the structural proposal, illustrating the power of integrated multi-technique approaches in unknown characterization.

References

1. Moorthy A., Wallace W., Kearsley A.J., Tchekhovskoi D., Stein S. Combining Fragment-Ion and Neutral-Loss Matching during Mass Spectral Library Searching: A New General Purpose Algorithm Applicable to Illicit Drug Identification. Analytical Chemistry. 2017;89(24):13261–13268.