Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Carlos Gueto-Tettay; Di Tang; Lotta Happonen; Moritz Heusel; Hamed Khakzad; Johan Malmström; Lars Malmström

doi:10.1371/journal.pcbi.1010457

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Open Access

Peer-reviewed

Research Article

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Carlos Gueto-Tettay,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Visualization, Writing – original draft, Writing – review & editing

Affiliation Division of Infection Medicine, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden

https://orcid.org/0000-0002-8496-6341

⨯
Di Tang,

Roles Investigation, Resources, Writing – original draft

Affiliation Division of Infection Medicine, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden

https://orcid.org/0000-0001-6323-9375

⨯
Lotta Happonen,

Roles Investigation, Resources, Writing – original draft

Affiliation Division of Infection Medicine, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
⨯
Moritz Heusel,

Roles Resources

Affiliation Division of Infection Medicine, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden

https://orcid.org/0000-0002-8506-530X

⨯
Hamed Khakzad,

Roles Formal analysis, Writing – original draft

Affiliation Université de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France

https://orcid.org/0000-0002-8556-0650

⨯
Johan Malmström,

Roles Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – original draft

Affiliation Division of Infection Medicine, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden
⨯
Lars Malmström

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Writing – original draft, Writing – review & editing

* E-mail: lars.malmstroem@med.lu.se

Affiliation Division of Infection Medicine, Department of Clinical Sciences Lund, Faculty of Medicine, Lund University, Lund, Sweden

https://orcid.org/0000-0001-9885-9312

⨯

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Carlos Gueto-Tettay,
Di Tang,
Lotta Happonen,
Moritz Heusel,
Hamed Khakzad,
Johan Malmström,
Lars Malmström

Published: January 20, 2023
https://doi.org/10.1371/journal.pcbi.1010457

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Proteases
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Deep learning
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Protein sequencing
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Serine proteases
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Chymotrypsin
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Monoclonal antibodies
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Pepsins
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