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PPI-ID: Streamlining protein-protein interaction prediction through domain and SLiM mapping.
Haley V Goodwin1,2, Nigel S Atkinson1,2
1Department of Neuroscience, University of Texas at Austin, Austin, Texas, United States of America.
Plos Computational Biology
|October 16, 2025
Summary
The Protein-Protein Interaction Identifier (PPI-ID) tool accurately maps protein interaction domains and motifs onto 3D structures. It enhances protein complex modeling by predicting and filtering potential protein-protein interactions (PPIs).
Area of Science:
- Structural biology
- Bioinformatics
- Computational biology
Background:
- Protein-protein interactions (PPIs) are crucial for cellular functions.
- Accurate prediction and structural modeling of PPIs are essential for understanding biological processes.
- Current methods for PPI prediction and structural modeling can be computationally intensive.
Purpose of the Study:
- To develop a tool for mapping interaction domains and motifs onto protein structures.
- To improve the accuracy and efficiency of protein complex modeling using AlphaFold-Multimer.
- To identify and label interacting amino acids within predicted protein complexes.
Main Methods:
- Developed the Protein-Protein Interaction Identifier (PPI-ID) tool.
- PPI-ID maps interaction domains and motifs onto molecular structures.
- Filters for domains and motifs sufficiently close to interact and labels interacting amino acids.
- Predicts regions for AlphaFold-Multimer modeling based on input sequences, requiring paired sequences for interaction reporting.
Main Results:
- PPI-ID successfully maps interaction domains and motifs onto molecular structures.
- The tool identifies and labels interacting amino acids at predicted interfaces.
- When given only sequences, PPI-ID effectively predicts regions for AlphaFold-Multimer modeling.
- Testing with known dimers confirmed the high accuracy of PPI-ID in predicting protein-protein interactions.
Conclusions:
- PPI-ID enhances protein complex modeling and protein-protein interaction (PPI) prediction.
- The tool provides structural insights into protein interactions by mapping domains and motifs.
- PPI-ID offers a more computationally efficient approach to modeling protein complexes by focusing on interacting regions.
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