Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification.

ABSTRACT: Compound identification in small-molecule research, such as untargeted metabolomics or exposome research, relies on matching tandem mass spectrometry (MS/MS) spectra against experimental or in silico mass spectral libraries. Most software programs use dot product similarity scores. Here we introduce the concept of MS/MS spectral entropy to improve scoring results in MS/MS similarity searches via library matching. Entropy similarity outperformed 42 alternative similarity algorithms, including dot product similarity, when searching 434,287 spectra against the high-quality NIST20 library. Entropy similarity scores proved to be highly robust even when we added different levels of noise ions. When we applied entropy levels to 37,299 experimental spectra of natural products, false discovery rate

SUBMITTER: Li Y 

PROVIDER: S-EPMC11492813 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature