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

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

15.2K
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...
15.2K
Conservation of Protein Domains02:26

Conservation of Protein Domains

4.4K
4.4K
Conserved Binding Sites01:49

Conserved Binding Sites

5.3K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
5.3K
Conserved Binding Sites01:49

Conserved Binding Sites

2.0K
2.0K
Spin–Spin Coupling Constant: Overview01:08

Spin–Spin Coupling Constant: Overview

1.7K
In bromoethane, the three methyl protons are coupled to the two methylene protons that are three bonds away. In accordance with the n+1 rule, the signal from the methyl protons is split into three peaks with 1:2:1 relative intensities. The methylene protons appear as a quartet, with the relative intensities of 1:3:3:1.
Qualitatively, any spin plus-half nucleus polarizes the spins of its electrons to the minus-half state. Consequently, the paired electron in the hydrogen–carbon bond must...
1.7K
Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.9K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
2.9K

You might also read

Related Articles

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

Sort by
Same author

Toward systems agroecology: Risk-reward balance, emergent plant communities, and temporal weather map in multiplant farming.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Compatibility of intracellular binding: Evolutionary design principles for metal sensors.

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

Engineering highly active nuclease enzymes with machine learning and high-throughput screening.

Cell systems·2025
Same author

Toward systems agroecology: Design and control of intercropping.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same author

How do you anticipate computational protein design will change biotechnology and therapeutic development?

Cell systems·2024
Same author

The Pfam protein families database: embracing AI/ML.

Nucleic acids research·2024
Same journal

DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotation.

PLoS computational biology·2026
Same journal

Redefining and estimating the early-phase reproduction ratio for epidemic outbreaks in spatially structured populations.

PLoS computational biology·2026
Same journal

Optimized phenotype definitions boost GWAS power.

PLoS computational biology·2026
Same journal

Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.

PLoS computational biology·2026
Same journal

Exploring the structural lexicon of the Proteome via Metric Geometry.

PLoS computational biology·2026
Same journal

Linking retinal sampling in neural encoding models to temporal profiles of visual processing in humans.

PLoS computational biology·2026
See all related articles

Related Experiment Video

Updated: Apr 16, 2026

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

5.9K

Protein sectors: statistical coupling analysis versus conservation.

Tiberiu Teşileanu1, Lucy J Colwell2, Stanislas Leibler3

  • 1The Simons Center for Systems Biology and The School of Natural Sciences, Institute for Advanced Study, Einstein Drive, Princeton, New Jersey, United States of America; Initiative for the Theoretical Sciences, CUNY Graduate Center, 365 Fifth Avenue, New York, New York, United States of America.

Plos Computational Biology
|February 28, 2015
PubMed
Summary
This summary is machine-generated.

Statistical coupling analysis (SCA) identifies protein sectors. However, sequence conservation, not coevolution, dominates SCA in single-sector proteins, limiting functional insights. Future research should focus on multi-sector proteins.

More Related Videos

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

7.8K
A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry
08:04

A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry

Published on: March 13, 2014

12.7K

Related Experiment Videos

Last Updated: Apr 16, 2026

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells
06:48

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

5.9K
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

7.8K
A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry
08:04

A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry

Published on: March 13, 2014

12.7K

Area of Science:

  • Computational Biology
  • Protein Bioinformatics
  • Molecular Evolution

Background:

  • Statistical coupling analysis (SCA) is a method to identify coevolving residue groups ('sectors') in protein alignments.
  • SCA combines correlation and sequence conservation for spectral analysis, with claimed functional significance for identified sectors.
  • Existing experimental validation predominantly involves proteins with only a single identified sector.

Purpose of the Study:

  • To re-evaluate the functional significance of protein sectors identified by SCA.
  • To investigate the influence of sequence conservation versus coevolution in SCA, particularly in single-sector proteins.
  • To propose a revised experimental strategy for SCA research.

Main Methods:

  • Reanalysis of existing experimental data on protein sectors.
  • Comparative analysis of SCA results focusing on sequence conservation and coevolutionary signals.
  • Statistical assessment of functional predictions based on conservation alone versus SCA.

Main Results:

  • In proteins with a single SCA sector, sequence conservation is the primary driver of the analysis.
  • Sequence conservation alone can yield statistically equivalent functional predictions compared to full SCA in single-sector cases.
  • The dominance of conservation in single-sector proteins may obscure true coevolutionary signals.

Conclusions:

  • The functional interpretation of SCA results requires careful consideration of the number of identified sectors.
  • Experimental focus should shift to proteins with multiple SCA sectors to better isolate coevolutionary effects.
  • This shift will enable a clearer understanding of protein correlations beyond simple sequence conservation.