Mad Hatter correctly annotates 98% of small molecule tandem mass spectra searching in PubChem

Abstract

AbstractMetabolites provide a direct functional signature of cellular state. Untargeted metabolomics usually relies on mass spectrometry, a technology capable of detecting thousands of compounds in a biological sample. Metabolite annotation is executed using tandem mass spectrometry. Spectral library search is far from comprehensive, and numerous compounds remain unannotated. So-calledin silicomethods allow us to overcome the restrictions of spectral libraries, by searching in much larger molecular structure databases. Yet, after more than a decade of method development,in silicomethods still do not reach correct annotation rates that users would wish for. Here, we present a novel computational method called MadHatterfor this task. MadHattercombines CSI:FingerID results with information from the searched structure database via a metascore. Compound information includes the melting point, and the number words in the compound description starting with the letter ‘u’. We then show that MadHatterreaches a stunning 97.6% correct annotations when searching PubChem, one of the largest and most comprehensive molecular structure databases. Finally, we explain what evaluation glitches were necessary for MadHatterto reach this annotation level, what is wrong with similar metascores in general, and why metascores may screw up not only method evaluations but also the analysis of biological experiments.