Modelling protein complexes with crosslinking mass spectrometry and deep learning.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 39251624.
- Also identified by DOI 10.1038/s41467-024-51771-2 and PMC identifier 11383924.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.
Medical subject headings
- Bacillus subtilis
- Mass Spectrometry
- Deep Learning
- Bacterial Proteins