Text Mining and Computational Chemistry Reveal Trends in Applications of Laser Desorption/Ionization Techniques to Small Molecules
- PMID: 39308355
- PMCID: PMC11457301
- DOI: 10.1021/jasms.4c00293
Text Mining and Computational Chemistry Reveal Trends in Applications of Laser Desorption/Ionization Techniques to Small Molecules
Abstract
Continued development of laser desorption/ionization (LDI) since its inception in the 1960s has produced an explosion of soft ionization techniques, where ionization is assisted by the physical or chemical properties of a structure or matrix. While many of these techniques have primarily been used to ionize large biomolecules, including proteins, some have recently seen increasing applications to small molecules such as pharmaceuticals. Small molecules pose particular challenges for LDI techniques, including interference from the matrix or support in the low mass range. To investigate trends in the application of soft LDI techniques to small molecules, we combined text mining and computational chemistry, looking specifically at matrix substances, analyte properties, and the research domain. In addition to making visible the history of LDI techniques, the results may inform the choice of method and suggest new avenues of method development. All software and collected data are freely available on GitHub (https://github.com/ReinV/SCOPE), VOSviewer (https://www.vosviewer.com), and OSF (https://osf.io/zkmua/).
Conflict of interest statement
The authors declare no competing financial interest.
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