PPI-ID: Streamlining protein-protein interaction prediction through domain and SLiM mapping
AlphaFold-Multimer models protein complexes and facilitates protein-protein interaction (PPI) prediction. Mapping of protein interaction domains and motifs onto the 3D structure can lend credence to the model and provide insight into the function of a given interaction. Furthermore, limiting structure prediction to only the domains and motifs that are likely to interact can reduce the computational demand and produce a higher quality model. To satisfy these needs, we built the Protein-Protein Interaction Identifier (PPI-ID). PPI-ID maps interaction domains and motifs onto molecular structures and filters for those that are sufficiently close to interact. Once an interface is found, PPI-ID labels interacting amino acids. Given only sequences, PPI-ID predicts regions for AlphaFold-Multimer modeling, reporting potential interactions only when each protein has one-half of a paired sequence. Testing with known dimers confirms high accuracy of the tool.
Authors
- Nigel S. Atkinson (ORCID: https://orcid.org/0000-0001-8963-7478)
- Haley V. Goodwin
Institutions
- The University of Texas at Austin (US)
Publication Details
- Journal
- PLoS Computational Biology
- Published
- 2025-10-16
- DOI
- https://doi.org/10.1371/journal.pcbi.1013062
- Citations
- 1
- Primary Topic
- Protein Structure and Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.81