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Related Concept Videos

Protein-protein Interfaces02:04

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 Interfaces02:04

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 Networks02:26

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 Networks02:26

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 Organization01:24

Protein Organization

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 Organization01:13

Protein Organization

Overview

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A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Integrating protein-protein interactions and text mining for protein function prediction.

Samira Jaeger1, Sylvain Gaudan, Ulf Leser

  • 1Knowledge Management in Bioinformatics, Humboldt-University Berlin, Unter den Linden 6, 10099 Berlin, Germany. sjaeger@informatik.hu-berlin.de

BMC Bioinformatics
|August 5, 2008
PubMed
Summary

This study presents a reliable method for predicting protein functions using conserved protein interaction graphs and literature mining. The approach accurately identifies Gene Ontology (GO) annotations for uncharacterized proteins.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Protein Science

Background:

  • Protein functional annotation is challenging, with literature curation being slow and costly.
  • Existing automatic methods lack sufficient reliability for accurate functional predictions.
  • There is a need for robust computational approaches to aid in protein function discovery.

Purpose of the Study:

  • To develop and validate a novel method for predicting protein functions.
  • To identify conserved protein interaction graphs for functional inference.
  • To predict missing Gene Ontology (GO) annotations using orthologs and literature data.

Main Methods:

  • Identification of conserved protein interaction graphs.
  • Prediction of protein functions based on orthologs within these graphs.
  • Validation of predictions using literature mining and expert curation.

Main Results:

  • Over 80% of existing Gene Ontology (GO) annotations for proteins with conserved orthologs were automatically verified.
  • New GO annotations were predicted for a subset of proteins with 100% precision, confirmed by curators.
  • The method demonstrated high reliability in predicting functional annotations.

Conclusions:

  • Integrating conserved conserved subgraph (CCS) identification with literature mining offers a highly reliable method for predicting GO annotations.
  • This approach is particularly effective for weakly characterized proteins possessing orthologs.
  • The developed technique significantly enhances the efficiency and accuracy of protein function annotation.