Mistle: bringing spectral library predictions to metaproteomics with an efficient search index.

ABSTRACT:

Motivation

Deep learning has moved to the forefront of tandem mass spectrometry-driven proteomics and authentic prediction for peptide fragmentation is more feasible than ever. Still, at this point spectral prediction is mainly used to validate database search results or for confined search spaces. Fully predicted spectral libraries have not yet been efficiently adapted to large search space problems that often occur in metaproteomics or proteogenomics.

Results

In this study, we showcase a workflow that uses Prosit for spectral library predictions on two common metaproteomes and implement an indexing and search algorithm, Mistle, to efficiently identify experimental mass spectra within the library. Hence, the workflow emulates a classic protein sequence database search with

SUBMITTER: Nowatzky Y 

PROVIDER: S-EPMC10313348 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature