Journal Article

Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation

Djokic, Milena, Geist, Johanna L, Welzel, Mareen, Schueler-Furman, Ora, Keller Valsecchi, Claudia Isabelle, Schäfer, Christian, Strom, Joelle M, Schumbera, Eric, Lee, Chop Yan, Varga, Julia K, Kumar, Manjeet, Luck, Katja, Hubrich, Dalmira, Gibson, Toby J, Polat, Feyza, Schönfeld, Jonas

2024

Overview

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. Synopsis Based on thorough benchmarking of AlphaFold-Multimer a strategy for structure prediction was developed and applied to 62 protein interactions linked to neurological disease. Six novel protein interfaces were further experimentally corroborated. AlphaFold-Multimer (AF) largely fails to predict structures of interacting proteins involving short linear motifs when using full length sequences. A prediction strategy was developed based on protein fragmentation, which boosts AF sensitivity at costs of specificity. Application of this strategy to 62 protein interactions linked to neurological disease resulted in 18 correct or likely correct structural models. Six novel protein interfaces were further supported by experiments. Based on thorough benchmarking of AlphaFold-Multimer a strategy for structure prediction was developed and applied to 62 protein interactions linked to neurological disease. Six novel protein interfaces were further experimentally corroborated.

• Publisher: Nature Publishing Group UK,Springer Nature
• Subject: AlphaFold / Benchmarking / Biomedical and Life Sciences / Carrier Proteins / EMBO10 / EMBO40 / Experimental Validation / Humans / Life Sciences / Linear Motifs / Membrane Proteins - metabolism / Protein Interaction Interface Prediction / Proteins - metabolism / Systems Biology