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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 Folding01:22

Protein Folding

Overview
Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...

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Related Experiment Video

Updated: May 26, 2026

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

Protein 3D structure computed from evolutionary sequence variation.

Debora S Marks1, Lucy J Colwell, Robert Sheridan

  • 1Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America. foldingproteins@cbio.mskcc.org

Plos One
|December 14, 2011
PubMed
Summary
This summary is machine-generated.

Researchers can infer evolutionary constraints from protein sequences to predict 3D protein structures. Co-evolutionary signals accurately determine protein folds, aiding in protein design and identifying genetic variants.

More Related Videos

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

Related Experiment Videos

Last Updated: May 26, 2026

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

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

Area of Science:

  • Computational Biology
  • Structural Biology
  • Evolutionary Biology

Background:

  • Protein function constrains evolutionary paths, with homologs recording evolutionary experiments.
  • Inferring evolutionary constraints from sequence homologs is challenging due to noise and correlations.

Purpose of the Study:

  • To infer evolutionary constraints from protein sequence homologs.
  • To distinguish true co-evolutionary couplings from noise.
  • To predict 3D protein structure from sequence data.

Main Methods:

  • Utilized a maximum entropy model of protein sequences.
  • Constrained the model using statistics from multiple sequence alignments.
  • Inferred residue pair couplings to predict structural proximity.

Main Results:

  • Inferred residue coupling strength accurately predicts residue-residue proximity in folded structures.
  • Top-scoring couplings were sufficient to define 3D protein folds.
  • Accurate de novo 3D protein structures were computed for fifteen proteins (50-260 residues) using co-evolution signals (EVfold).

Conclusions:

  • Co-evolutionary signals contain sufficient information to determine accurate 3D protein structures.
  • This method provides insights into protein evolution and interactions.
  • Facilitates protein structure surveys, protein/drug design, and identification of functional genetic variants.