ArticleNature communications2024
From interaction networks to interfaces, scanning intrinsically disordered regions using AlphaFold2.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed.
- HighFold4: extending AlphaFold3 to accurate cyclic peptide conformation prediction via custom chemical connectivity.Briefings in bioinformatics · 2026Article
- Human PMS1-dependent non-canonical mismatch repair engages with MBD4 to repair methylated CpG deamination.Nucleic acids research · 2026Article
- Variant characterization in the intrinsically disordered human proteome.Nature structural & molecular biology · 2026Article
- When can AlphaFold predict the oligomeric states of proteins?Protein science : a publication of the Protein Society · 2026Article
- Structuring Disorder via Supervised Molecular Dynamics: Uncovering Arginine-Glycine-Glycine-Mediated Ribonucleic Acid-Intrinsically Disordered Region Recognition Mechanisms.Journal of chemical information and modeling · 2026Article
- Systematic discovery of motif-based interactions of the auxiliary domains of USP family deubiquitinases.Nature communications · 2026Article
- Functional flexibility in bacterial hub proteins is driven by proteome expansion.Scientific reports · 2026Article
- AlphaFold-driven discovery of oxysterol-binding protein-related protein-phosphoinositide 3-, 4-, and 5-phosphatase interactions using new generation confidence scores.Protein science : a publication of the Protein Society · 2026Article
- PPIscreenML is a method for structure-based screening of protein-protein interactions using AlphaFold.eLife · 2026Article
- Hierarchical decoding of targeting tripeptide motif by the cytosolic iron-sulfur cluster assembly targeting complex.bioRxiv : the preprint server for biology · 2026Article
- A Survey of Predicted Protein-Protein Interactions Involving Disordered Regions in Humans.Journal of molecular biology · 2026Article
- Detection of Mutation-Induced Conformational Changes in an Intrinsically Disordered Protein by Double Quantum Coherence Electron Spin Resonance Methodology.Journal of the American Chemical Society · 2026Article
- Non-covalent SUMO interactions with ligases and effectors: SUMO-interacting motifs and beyond.Essays in biochemistry · 2025Review
- AlphaFold-Guided Discovery of an Overlapping MYC/Miz-1 Interface Enables Peptidomimetic Disruption of MYC/MAX.ChemMedChem · 2025Article
- Structural details of helix-mediated multimerization of the conserved region of TDP-43 C-terminal domain.Nature communications · 2025Article
- Definition and Discovery of Tandem SH3-Binding Motifs Interacting with Members of the p47Biomolecules · 2025Article
- Simulated Solute Tempering 2: An Efficient and Practical Approach to Protein Conformational Sampling and Binding Events.Journal of chemical theory and computation · 2025Article
- The composition and structure of the outer kinetochore KMN complex is conserved across kingdoms.Communications biology · 2025Article
- Assessing scoring metrics for AlphaFold2 and AlphaFold3 protein complex predictions.Protein science : a publication of the Protein Society · 2025Article
- Training bias and sequence alignments shape protein-peptide docking by AlphaFold and related methods.Protein science : a publication of the Protein Society · 2025Article
2 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors.
Funding
Abstract
The revolution brought about by AlphaFold2 opens promising perspectives to unravel the complexity of protein-protein interaction networks. The analysis of interaction networks obtained from proteomics experiments does not systematically provide the delimitations of the interaction regions. This is of particular concern in the case of interactions mediated by intrinsically disordered regions, in which the interaction site is generally small. Using a dataset of protein-peptide complexes involving intrinsically disordered regions that are non-redundant with the structures used in AlphaFold2 training, we show that when using the full sequences of the proteins, AlphaFold2-Multimer only achieves 40% success rate in identifying the correct site and structure of the interface. By delineating the interaction region into fragments of decreasing size and combining different strategies for integrating evolutionary information, we manage to raise this success rate up to 90%. We obtain similar success rates using a much larger dataset of protein complexes taken from the ELM database. Beyond the correct identification of the interaction site, our study also explores specificity issues. We show the advantages and limitations of using the AlphaFold2 confidence score to discriminate between alternative binding partners, a task that can be particularly challenging in the case of small interaction motifs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.