Modelling protein complexes with crosslinking mass spectrometry and deep learning

Kolja Stahl, Robert Warneke, Lorenz Demann, Rica Bremenkamp, Björn Hormes, Oliver Brock, Jörg Stülke () and Juri Rappsilber ()
Additional contact information
Kolja Stahl: Chair of Bioanalytics
Robert Warneke: GZMB
Lorenz Demann: GZMB
Rica Bremenkamp: GZMB
Björn Hormes: GZMB
Oliver Brock: Robotics and Biology Laboratory
Jörg Stülke: GZMB
Juri Rappsilber: Chair of Bioanalytics

Nature Communications, 2024, vol. 15, issue 1, 1-10

Abstract: Abstract Scarcity of structural and evolutionary information on protein complexes poses a challenge to deep learning-based structure modelling. We integrate experimental distance restraints obtained by crosslinking mass spectrometry (MS) into AlphaFold-Multimer, by extending AlphaLink to protein complexes. Integrating crosslinking MS data substantially improves modelling performance on challenging targets, by helping to identify interfaces, focusing sampling, and improving model selection. This extends to single crosslinks from whole-cell crosslinking MS, opening the possibility of whole-cell structural investigations driven by experimental data. We demonstrate this by revealing the molecular basis of iron homoeostasis in Bacillus subtilis.

Date: 2024
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DOI: 10.1038/s41467-024-51771-2

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