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Spectral Matching Vs. in-silico Fragment Matching – Rendering Confidence to Bio-therapeutic Glycan Characterization

Spectral Pattern Matching

January 13, 2020

Recent advances in the field of mass spectrometry has opened new dimensions in biopharmaceutical and biomedical analysis. Monoclonal antibodies (mAbs) are acting as a driving force in the growth of the biopharmaceutical industry. Monosaccharide compositions, glycosidic linkages, and abundances of glycans in the glycoprotein molecules are now important for understanding the efficacy and batch-to-batch consistency of different drugs. This has led to the evolution of tandem MS (MS/MS) technique, which is proven to be more successful compared to the first stage mass spectrometry (Full MS) technique.

The conventional MS/MS-based identification strategy involves identifying candidate glycan structures based on the number of theoretical fragments (related to the glycan structure) present in the experimental MS/MS spectrum. This technique needs all possible theoretical fragments of a glycan to be available to compare with the experimental fragments. Over time, it was realized that this in-silico fragment matching strategy works well for discovery analysis, however, may not be an ideal approach for the bio-pharmaceutical industry because of the type of the molecules they work with and the workflows they employ. Biopharmas follow a targeted analysis workflow on pre-characterized molecules, and hence adopting a time consuming de novo identification strategy may not be justified.

A new technique, spectral pattern matching addresses these challenges. The process involves creating a spectral library with the help of pre-analyzed glycan standards under a set of instrumental and experimental conditions. The reference spectra contains more precise fragment information compared to in-silico fragments, which makes the identification more confident and time-efficient. Apart from the individual in-silico matching and spectral matching algorithms, certain software products, such as GlycanExplorerTM, are equipped with a unique search mechanism that renders dual confidence to the glycan identification.

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