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Protein-protein Interfaces

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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...

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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Published on: January 26, 2024

A survey on computational models for predicting protein-protein interactions.

Lun Hu¹, Xiaojuan Wang², Yu-An Huang³

¹Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, 830011, Urumqi, China.

Briefings in Bioinformatics

|March 11, 2021

Summary

Computational models can predict protein-protein interactions (PPIs) more efficiently than lab experiments. This survey reviews algorithms, validation methods, and databases for improved PPI prediction accuracy.

Keywords:

biological databases computational prediction models performance evaluation protein–protein interaction

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Last Updated: Nov 14, 2025

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Published on: January 26, 2024

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

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A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

Computational Biology
Bioinformatics
Systems Biology

Background:

Protein-protein interactions (PPIs) are fundamental to cellular processes.
Laboratory methods for PPI detection are time-consuming, labor-intensive, and can yield uncertain results.
High-throughput technologies generate vast proteomics data, necessitating computational approaches for PPI prediction.

Purpose of the Study:

To provide a comprehensive survey of computational models for predicting protein-protein interactions (PPIs).
To classify existing algorithms and discuss their relative merits.
To highlight validation strategies, common databases, and future research directions in PPI prediction.

Main Methods:

Categorization of algorithms used for computational PPI prediction.
Discussion of validation schemes and performance metrics for evaluating prediction models.
Description of biological databases commonly employed for comparative analysis.

Main Results:

Identification and classification of various computational approaches for PPI prediction.
Analysis of different validation strategies and metrics for assessing model performance.
Overview of commonly used biological databases for PPI data.

Conclusions:

Computational models offer a powerful alternative to experimental methods for PPI prediction.
Effective validation schemes and appropriate databases are crucial for accurate PPI prediction.
Addressing open issues in PPI prediction is essential for future advancements in the field.