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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.
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,...

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,...

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 polypeptide...

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 polypeptide...

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...

Protein Families

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism. Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members. If these new proteins contain similar amino acids in key locations, protein...

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Related Experiment Video

Updated: Jun 2, 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

Scoring protein relationships in functional interaction networks predicted from sequence data.

Gaston K Mazandu¹, Nicola J Mulder

¹Computational Biology Group, Department of Clinical Laboratory Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.

|April 29, 2011

Summary

This summary is machine-generated.

This study introduces novel computational methods to predict protein functions using sequence and domain information. These methods create a functional network for Mycobacterium tuberculosis, aiding in the discovery of uncharacterized protein functions.

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A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

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

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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Diverse biological data, primarily protein sequences and domains, hold vast potential for understanding organisms.
Computational methods are crucial for integrating and analyzing this data to predict protein functions and relationships.
Predicting functions of uncharacterized proteins is essential for maximizing knowledge gained from sequencing efforts.

Purpose of the Study:

To develop and apply information-theoretic approaches for scoring protein-protein functional interaction pairs.
To predict functional relationships based on protein sequence similarity and conserved domain matches.
To construct a high-confidence functional network for Mycobacterium tuberculosis to infer functions of uncharacterized proteins.

Main Methods:

Utilized information-theoretic methods to score protein-protein functional interactions.
Employed protein sequence similarity and conserved protein signature matches for prediction.
Applied scoring schemes to the Mycobacterium tuberculosis proteome to build a functional network.

Main Results:

Developed effective data-driven scoring schemes for protein-protein functional connections.
Generated a homology-based functional network for Mycobacterium tuberculosis with high confidence and coverage.
Demonstrated the utility of the network for predicting functions of uncharacterized proteins.

Conclusions:

Information-theoretic approaches provide a robust framework for scoring protein-protein functional interactions.
The developed functional network facilitates the prediction of protein functions in Mycobacterium tuberculosis.
This work enhances the exploitation of biological sequence data for functional inference.