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Modelling protein complexes with crosslinking mass spectrometry and deep learning

Year: 2024

Type: article

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 .

Source: DepositOnce

DOI: 10.14279/depositonce-22824

Authors: Stahl, Kolja, Warneke, Robert, Demann, Lorenz, Bremenkamp, Rica, Hormes, Björn, Brock, Oliver, Stülke, Jörg, Rappsilber, Juri

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W6904584739

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