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Generalizable Direct Protein Sequencing With InstaNexus

Journal Article (2026)
Author(s)

Marco Reverenna (Technical University of Denmark (DTU))

Maike Wennekers Nielsen (Technical University of Denmark (DTU))

Darian Stephan Wolff (Technical University of Denmark (DTU), Novonesis)

Jemma Daniel (InstaDeep Ltd)

Elpida Lytra (Technical University of Denmark (DTU))

Suthimon Thumtecho (Technical University of Denmark (DTU))

Pasquale D. Colaianni (Technical University of Denmark (DTU))

Alberto Santos (Technical University of Denmark (DTU))

Konstantinos Kalogeropoulos (Technical University of Denmark (DTU), Kavli institute of nanoscience Delft, TU Delft - Applied Sciences)

More Authors (External organisation)

Research Group
BN/Stan Brouns Lab
DOI related publication
https://doi.org/10.1016/j.mcpro.2026.101547 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
BN/Stan Brouns Lab
Journal title
Molecular & cellular proteomics : MCP
Issue number
4
Volume number
25
Pages (from-to)
101547
Downloads counter
4
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Abstract

Accurate determination of protein sequences is central to biology. Protein-based therapeutics, such as antibodies and nanobodies, are not encoded in reference genomes, challenging their accurate characterization via standard proteomics. Current methods rely on indirect inference, fragmented outputs, and labor-intensive workflows, which hinder functional insights and routine application. Here, we present a generalizable, end-to-end workflow for direct protein sequencing, combining streamlined sample preparation, artificial intelligence (AI)-driven de novo peptide sequencing, and tailored assembly to reconstruct contiguous protein sequences. A novel composite scoring framework prioritizes longer assemblies and coverage, enhancing accuracy and reducing ambiguity. Validation across diverse protein modalities demonstrates its utility and ability to robustly sequence functionally critical regions of selected proteins. This workflow represents an advance in precision proteomics with promising applications in therapeutic discovery, immune profiling, and protein science.