Publications by authors named "John A Cormican"

If and how proteasomes catalyze not only peptide hydrolysis but also peptide splicing is an open question that has divided the scientific community. The debate has so far been based on immunopeptidomics, in vitro digestions of synthetic polypeptides as well as ex vivo and in vivo experiments, which could only indirectly describe proteasome-catalyzed peptide splicing of full-length proteins. Here we develop a workflow-and cognate software - to analyze proteasome-generated non-spliced and spliced peptides produced from entire proteins and apply it to in vitro digestions of 15 proteins, including well-known intrinsically disordered proteins such as human tau and α-Synuclein.

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Article Synopsis
  • Noncanonical epitopes presented by HLA-I complexes are gaining attention for developing new immunotherapies targeting cancer, infections, and autoimmune conditions.
  • In this study, researchers created an extensive database of peptides generated by proteasomes, including spliced and non-spliced variants, by analyzing 80 synthetic polypeptide substrates using mass spectrometry.
  • The resulting database contains 16,631 unique peptides, offering valuable data for predicting how proteasomes produce and process these peptides, alongside discussions on potential biases in the identification methods.
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Rescoring of mass spectrometry (MS) search results using spectral predictors can strongly increase peptide spectrum match (PSM) identification rates. This approach is particularly effective when aiming to search MS data against large databases, for example, when dealing with nonspecific cleavage in immunopeptidomics or inflation of the reference database for noncanonical peptide identification. Here, we present inSPIRE (in silico Spectral Predictor Informed REscoring), a flexible and performant open-source rescoring pipeline built on Prosit MS spectral prediction, which is compatible with common database search engines.

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The discovery of many noncanonical peptides detectable with sensitive mass spectrometry inside, outside, and on cells shepherded the development of novel methods for their identification, often not supported by a systematic benchmarking with other methods. We here propose iBench, a bioinformatic tool that can construct ground truth proteomics datasets and cognate databases, thereby generating a training court wherein methods, search engines, and proteomics strategies can be tested, and their performances estimated by the same tool. iBench can be coupled to the main database search engines, allows the selection of customized features of mass spectrometry spectra and peptides, provides standard benchmarking outputs, and is open source.

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Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry (MS) required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes.

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