ABSTRACT
This manuscript outlines a straight-forward procedure for generating a map of similarity between spectra of a set. When applied to a reference set of spectra for Type I fentanyl analogs (molecules differing from fentanyl by a single modification), the map illuminates clustering that is applicable to automated structure assignment of unidentified molecules. An open-source software implementation that generates mass spectral similarity mappings of unknowns against a library of Type I fentanyl analog spectra is available at http://github.com/asm3-nist/FentanylClassifier.
ABSTRACT
A comprehensive database of gas chromatographic retention properties of chemical compounds has been developed using multiple literature sources. The National Institute of Standards and Technology (NIST) database of retention data for non-polar and polar stationary phases currently contains 292,924 data records for 42,888 compounds. The database includes data for Kováts indices, linear indices, Lee indices, retention times and retention volumes. The first release of this database for non-polar stationary phases is available with NIST/US Environmental Protection Agency (EPA)/National Institutes of Health (NIH) Mass Spectral Database (June 2005) and through the internet (NIST Chemistry WebBook). The paper describes the database and the process by which it has been compiled. The format of data presentation and the quality control procedures are described. Data sources of gas chromatographic retention data are also discussed.
Subject(s)
Chromatography, Gas/methods , Database Management Systems , Organic Chemicals/chemistryABSTRACT
The National Institute of Standards and Technology (NIST) Automated Mass Spectral Deconvolution and Identification System (AMDIS) is applied to a selection of data files obtained from the gas chromatography/mass spectrometry (GC/MS) analysis of urinary organic acids. Mass spectra obtained after deconvolution are compared with a special user library containing both the mass spectra and retention indices of ethoxime-trimethylsilyl (EO-TMS) derivatives of a set of organic acids. Efficient identification of components is achieved and the potential of the procedure for automated diagnosis of inborn errors of metabolism and for related research is demonstrated.