Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Protein Organization01:24

Protein Organization

6.0K
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....
6.0K
Globular and Fibrous Proteins02:21

Globular and Fibrous Proteins

43.0K
Many proteins can be classified into two distinct subtypes - globular or fibrous. These two types differ in their shapes and solubilities.
Globular proteins are also known as spheroproteins and typically are approximately round in shape. They contain a mix of amino acid types and contain differing sequences in their primary structures. Globular proteins have many different functions, such as enzymes, cellular messengers, and molecular transporters. These roles often require the proteins to be...
43.0K
Protein and Protein Structure02:15

Protein and Protein Structure

77.5K
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...
77.5K
Protein Families02:47

Protein Families

15.2K
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...
15.2K
Protein Networks02:26

Protein Networks

3.9K
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,...
3.9K
Protein and Protein Structures02:15

Protein and Protein Structures

10.2K
10.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Reversible molecular simulation for training classical and machine-learning force fields.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Data-driven regularization lowers the size barrier of cryo-EM structure determination.

Nature methods·2024
Same author

Differentiable simulation to develop molecular dynamics force fields for disordered proteins.

Chemical science·2024
Same author

Automated model building and protein identification in cryo-EM maps.

Nature·2024
Same author

Rapid discovery of high-affinity antibodies via massively parallel sequencing, ribosome display and affinity screening.

Nature biomedical engineering·2023
Same author

Automated model building and protein identification in cryo-EM maps.

bioRxiv : the preprint server for biology·2023
Same journal

MOREshiny: a user-friendly application for the inference of phenotype-specific multi-omic regulatory networks.

Bioinformatics advances·2026
Same journal

spammR: an R package designed for analysis and integration of spatial multi-omic measurements.

Bioinformatics advances·2026
Same journal

Interpretable prediction and generation of ASC-speck aptamers using multiscale deep biological learning models.

Bioinformatics advances·2026
Same journal

vClassifier: a toolkit for high-resolution phylogenetic classification of prokaryotic viruses.

Bioinformatics advances·2026
Same journal

GWAIS-Web: a free and secure web service for ultra-fast and large-scale genome-wide association interaction studies.

Bioinformatics advances·2026
Same journal

Folding the unfoldable 2: using AlphaFold and ESMFold to explore spurious proteins.

Bioinformatics advances·2026
See all related articles

Related Experiment Video

Updated: May 15, 2025

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

15.3K

Fast protein structure searching using structure graph embeddings.

Joe G Greener1, Kiarash Jamali1

  • 1Medical Research Council Laboratory of Molecular Biology, Cambridge, CB2 0QH, United Kingdom.

Bioinformatics Advances
|April 8, 2025
PubMed
Summary
This summary is machine-generated.

We developed Progres, a fast protein structure search method using graph neural networks. It enables efficient comparison and classification of protein domains, aiding in remote homology detection and function annotation.

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

68.4K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.2K

Related Experiment Videos

Last Updated: May 15, 2025

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

15.3K
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

68.4K
Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

7.2K

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Machine learning in biology

Background:

  • Comparing protein structures independent of sequence is vital for understanding protein function and evolution.
  • The rapid growth of protein structure databases necessitates efficient search tools.
  • Existing methods face challenges in speed and accuracy for large-scale structure comparisons.

Purpose of the Study:

  • To develop a fast and accurate method for searching and comparing protein structures.
  • To create a low-dimensional embedding for protein domains using graph neural networks.
  • To facilitate remote homology detection, function annotation, and protein classification.

Main Methods:

  • Training a graph neural network (GNN) using supervised contrastive learning.
  • Learning low-dimensional embeddings of protein domains.
  • Implementing the Progres method as software and a web server.

Main Results:

  • Achieved accuracy comparable to state-of-the-art methods.
  • Demonstrated the ability to search protein domains in the AlphaFold database rapidly.
  • Enabled searching TED domains in a tenth of a second per query on CPU.

Conclusions:

  • Progres offers a significant advancement in protein structure searching speed and accuracy.
  • The method is valuable for exploring large structural datasets like AlphaFold.
  • Progres supports key bioinformatics tasks such as homology detection and functional annotation.