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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...

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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.
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Protein Organization

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

Protein Organization

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Updated: Mar 3, 2026

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

COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction

Chengxin Zhang¹, Lydia Freddolino^1,2, Yang Zhang^1,2

¹Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.

Nucleic Acids Research

|May 5, 2017

Summary

This summary is machine-generated.

The COFACTOR web server enhances protein function prediction using structure and sequence data. This improved hybrid approach boosts accuracy, especially for proteins lacking close evolutionary relatives.

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Area of Science:

Computational biology
Bioinformatics
Structural biology

Background:

Protein function prediction is crucial for understanding biological systems.
Existing methods often struggle with proteins lacking clear homology.
Structure-based approaches offer a complementary view.

Purpose of the Study:

To enhance the COFACTOR web server for improved protein function prediction.
To integrate sequence profile alignments and protein-protein interaction networks into function inference.
To evaluate the performance of the updated hybrid approach.

Main Methods:

Utilizing structure-based threading through the BioLiP library.
Developing new pipelines for sequence profile alignments.
Incorporating protein-protein interaction network data.
Performing large-scale benchmark tests.

Main Results:

The hybrid COFACTOR approach significantly improves function annotation accuracy.
Enhanced performance is particularly notable for proteins with no close homology.
The updated server outperforms previous versions and other state-of-the-art methods.
Successful inference of gene ontology, enzyme commission, and ligand-binding sites.

Conclusions:

The hybrid COFACTOR server provides a more accurate and robust method for protein function prediction.
Integrating diverse data types (structure, sequence, network) is key to improving functional annotation.
The updated COFACTOR server is a valuable resource for the research community.