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Related Concept Videos

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
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
Protein and Protein Structure02:15

Protein and Protein Structure

Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme can...
Protein Families02:47

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 23, 2026

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

Improving classification in protein structure databases using text mining.

Antonis Koussounadis1, Oliver C Redfern, David T Jones

  • 1Bioinformatics Group, Department of Computer Science, University College of London, London, WC1E 6BT, UK. a.koussounadis@cs.ucl.ac.uk

BMC Bioinformatics
|May 7, 2009
PubMed
Summary
This summary is machine-generated.

A new text-based method improves protein domain classification by analyzing document similarity. This approach aids in classifying borderline cases, enhancing accuracy and coverage beyond traditional structure and sequence comparisons.

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Last Updated: Jun 23, 2026

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

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Protein domain classification in CATH relies on structure, sequence, and manual review.
  • Evaluating borderline cases requires extensive literature review, creating a bottleneck.
  • There is a need for tools to help users quickly identify functional information from text for protein classification.

Purpose of the Study:

  • To present a text-based method for protein classification.
  • To complement existing sequence and structure-based approaches, especially for borderline cases.
  • To leverage textual similarity to infer biological function and aid classification decisions.

Main Methods:

  • An optimal text comparison strategy was identified using a gold standard enzyme dataset.
  • Machine learning filtered abstracts to identify relevant functional, structural, and classification information.
  • A combined structure and text similarity approach was tested on borderline protein domains.

Main Results:

  • Incorporating text similarity into logistic regression models significantly improved classification performance.
  • Coverage increased by 15.3% for the combined classifier versus 10% for the structural classifier alone at a 10-3 error rate.
  • The combined classifier made an additional 4.2% of correct decisions when using only the highest scoring predictions.

Conclusions:

  • A novel text-based method for protein domain classification has been developed.
  • This method improves upon existing approaches by directly incorporating structural and text-based classifiers.
  • The approach is particularly valuable for classifying protein domains with inconclusive sequence or structure similarity, reducing manual effort.