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,...
Conserved Binding Sites01:49

Conserved Binding Sites

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 analyses the...
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...
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.

You might also read

Related Articles

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

Sort by
Same author

Heterogeneity in symptom burden and supportive care needs among older adults with ischemic stroke: a cross-sectional study.

BMC geriatrics·2026
Same author

The modifying effect of diabetes on the association between triglyceride to high-density lipoprotein cholesterol ratio and cardiovascular risk: a systematic review and meta-analysis.

Frontiers in cardiovascular medicine·2026
Same author

Fermentative iron reduction by a psychrotolerant Clostridium-dominant consortium enriched from Antarctic penguin-impacted soils.

Communications biology·2026
Same author

Oliceridine versus sufentanil: a systematic review and meta-analysis of postoperative nausea and vomiting.

BMC anesthesiology·2026
Same author

Breaking the barrier: from biosynthetic inhibition to multidimensional modulation of the mycobacterial cell wall in tuberculosis therapy.

Frontiers in pharmacology·2026
Same author

ChSCL9 negatively regulates citric acid accumulation via repressing PH4-PH5 module in kumquat.

Plant physiology·2026

Related Experiment Video

Updated: Jul 11, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Improving protein protein interaction prediction based on phylogenetic information using a least-squares support

Roger A Craig1, Li Liao

  • 1Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA.

Annals of the New York Academy of Sciences
|October 11, 2007
PubMed
Summary

This study introduces a novel bioinformatics method for predicting protein-protein interactions using phylogenetic vectors and intra-matrix correlations. The new approach significantly improves prediction accuracy compared to existing methods.

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

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

Related Experiment Videos

Last Updated: Jul 11, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

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

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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Predicting protein-protein interactions is crucial for understanding cellular functions and biological networks.
  • Experimental methods for identifying protein interactions are time-consuming and expensive.
  • Computational approaches, particularly those using coevolutionary information, are actively being developed.

Purpose of the Study:

  • To develop a novel computational method for predicting protein-protein interactions.
  • To improve the accuracy of protein-protein interaction prediction by accounting for intra-matrix correlations.
  • To validate the proposed method using known protein interaction data.

Main Methods:

  • Utilized coevolutionary information from distance matrices of protein orthologs across reference genomes.
  • Transformed and concatenated distance matrices into phylogenetic vectors.
  • Employed a least-squares support vector machine with a weighted linear kernel to analyze phylogenetic vectors.

Main Results:

  • The novel method achieved a high receiver operator characteristic (ROC) score of 0.928 in cross-validation experiments.
  • This represents a significant improvement over methods relying solely on Pearson correlations (ROC score 0.659).
  • The weighted linear kernel effectively accounted for intra-matrix correlations, enhancing predictive power.

Conclusions:

  • The proposed method offers a more accurate and efficient approach for predicting protein-protein interactions.
  • Accounting for intra-matrix correlations is a key factor in improving computational prediction models.
  • This advancement contributes to the reverse-engineering of biological networks and understanding cellular mechanisms.