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Protein-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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Updated: Jun 9, 2025

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

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Published on: March 3, 2015

Accelerating protein-protein interaction screens with reduced AlphaFold-Multimer sampling.

Greta Bellinzona¹, Davide Sassera^1,2, Alexandre M J J Bonvin³

¹Department of Biology and Biotechnology, University of Pavia, Pavia 27100, Italy.

Bioinformatics Advances

|October 28, 2024

Summary

This summary is machine-generated.

Reducing AlphaFold-Multimer models speeds up protein-protein interaction (PPI) predictions without losing accuracy. This offers an efficient and eco-friendly approach for large-scale PPI discovery.

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Area of Science:

Computational structural biology
Bioinformatics
Systems biology

Background:

Protein-protein interactions (PPIs) are crucial for understanding cellular functions and biological systems.
Advances in computational tools like AlphaFold-Multimer aid in predicting PPIs.
Scaling PPI prediction for proteome-wide analysis presents computational challenges.

Purpose of the Study:

To assess the impact of reducing AlphaFold-Multimer models on PPI prediction accuracy.
To develop a faster and more resource-efficient method for large-scale PPI discovery.

Main Methods:

Evaluation of AlphaFold-Multimer with a single model output versus the standard five.
Testing on a diverse dataset of intra- and inter-species PPIs from bacterial and eukaryotic sources.

Main Results:

Reducing the number of generated models from five to one did not compromise the accuracy of distinguishing true from false PPIs.
The streamlined approach maintains high accuracy for both bacterial and eukaryotic protein interactions.

Conclusions:

A single model output from AlphaFold-Multimer is sufficient for accurate PPI prediction.
This optimization provides a faster, efficient, and environmentally friendly solution for large-scale PPI discovery.