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-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,...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Multi-pass Transmembrane Proteins and β-barrels01:09

Multi-pass Transmembrane Proteins and β-barrels

In multi-pass transmembrane proteins, the polypeptide chain crosses the membrane more than once. The transmembrane polypeptide chain either forms an α-helix or β-strand structure. α-Helix containing multi-pass transmembrane proteins are ubiquitous, whereas β-strand containing ones are mainly found in gram-negative bacteria, mitochondria, and chloroplasts.
α-Helix containing multi-pass transmembrane proteins
Multi-pass transmembrane proteins such as G-protein-linked receptors (GPCRs) and...

You might also read

Related Articles

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

Sort by
Same author

Integrating Past and Present <i>PHAGE</i> Research.

PHAGE (New Rochelle, N.Y.)·2026
Same author

On the Low Abundance of Antibiotic Resistance Genes in Bacteriophage Genomes and Their Random Acquisition via Specialized Transduction.

Genome biology and evolution·2026
Same author

Molecular maps of diseases from omics data and network embeddings.

NPJ systems biology and applications·2026
Same author

Genome characterization of <i>Salmonella enterica</i> serovar Enteritidis phage SESL from a Malaysian hot spring salt lick.

Microbiology resource announcements·2026
Same author

From Catheters to Capsids-New Insights from the Phage Frontier.

PHAGE (New Rochelle, N.Y.)·2026
Same author

Large-scale analysis of bacterial genomes reveals thousands of lytic phages.

Nature microbiology·2025
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 22, 2026

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

InterMap3D: predicting and visualizing co-evolving protein residues.

Rodrigo Gouveia-Oliveira1, Francisco S Roque, Rasmus Wernersson

  • 1Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark. gorm@cbs.dtu.dk

Bioinformatics (Oxford, England)
|June 17, 2009
PubMed
Summary
This summary is machine-generated.

InterMap3D predicts co-evolving protein residues using sequence alignments and visualizes them on 3D protein structures. This tool aids in understanding protein function and evolution by highlighting functionally important residue interactions.

More Related Videos

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

Related Experiment Videos

Last Updated: Jun 22, 2026

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

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

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Molecular modeling

Background:

  • Predicting co-evolving residues is crucial for understanding protein function and evolution.
  • Existing methods may require manual input or lack comprehensive visualization.
  • The Protein Data Bank (PDB) is a key resource for 3D protein structures.

Purpose of the Study:

  • To develop and present InterMap3D, a novel tool for predicting and visualizing co-evolving protein residues.
  • To automate the process of identifying homologous sequences and fetching relevant 3D structures.
  • To provide a user-friendly platform for analyzing protein residue co-evolution.

Main Methods:

  • Automated identification of homologous sequences from a single input sequence.
  • Generation of multiple sequence alignments.
  • Fetching of homologous 3D protein structures from the Protein Data Bank (PDB).
  • Prediction of co-evolving residues using three distinct computational methods: Row and Column Weighing of Mutual Information, Mutual Information/Entropy, and Dependency.
  • Visualization of predicted co-evolving residues on 3D protein structures.

Main Results:

  • InterMap3D successfully predicts co-evolving residues from sequence alignments.
  • The tool automatically retrieves relevant protein sequences and 3D structures.
  • Co-evolving residues are accurately mapped and highlighted on high-quality 3D protein models.
  • The system supports both automatically generated and user-provided alignments.

Conclusions:

  • InterMap3D offers an automated and integrated approach to predict and visualize protein residue co-evolution.
  • The tool enhances the analysis of protein structure-function relationships and evolutionary insights.
  • InterMap3D provides a valuable resource for researchers in structural biology and bioinformatics.