# Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation

Article · Chop Yan Lee, Dalmira Hubrich, Julia K. Varga, Christian Schäfer, Mareen Welzel, Eric Schumbera, Milena Djokic, Joelle Morgan Strom, Jonas Schönfeld, Johanna Lena Geist, Feyza Polat Haas, Toby J. Gibson, Claudia Isabelle Keller Valsecchi, Manjeet Kumar, Ora Schueler‐Furman, Katja Luck

- Archive id: doi:10.1038/s44320-023-00005-6
- Published: 2024-01-15
- Venue: Molecular Systems Biology
- DOI: https://doi.org/10.1038/s44320-023-00005-6
- PMID: 38225382
- PMCID: PMC10883280
- Citations: 105
- Source URL: https://doi.org/10.1038/s44320-023-00005-6
- PDF: https://europepmc.org/articles/PMC10883280/pdf
- Provenance: openalex+europepmc

## Abstract

Structural resolution of protein interactions enables mechanistic and functional studies as well as interpretation of disease variants. However, structural data is still missing for most protein interactions because we lack computational and experimental tools at scale. This is particularly true for interactions mediated by short linear motifs occurring in disordered regions of proteins. We find that AlphaFold-Multimer predicts with high sensitivity but limited specificity structures of domain-motif interactions when using small protein fragments as input. Sensitivity decreased substantially when using long protein fragments or full length proteins. We delineated a protein fragmentation strategy particularly suited for the prediction of domain-motif interfaces and applied it to interactions between human proteins associated with neurodevelopmental disorders. This enabled the prediction of highly confident and likely disease-related novel interfaces, which we further experimentally corroborated for FBXO23-STX1B, STX1B-VAMP2, ESRRG-PSMC5, PEX3-PEX19, PEX3-PEX16, and SNRPB-GIGYF1 providing novel molecular insights for diverse biological processes. Our work highlights exciting perspectives, but also reveals clear limitations and the need for future developments to maximize the power of Alphafold-Multimer for interface predictions.

_Abstract reproduced under CC-BY (publisher license, via OpenAlex)._

Topics: [AI Protein Design & Structure Prediction](https://space-kitty.com/topics/protein-design)

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