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

12.5K
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...
12.5K
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 Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

2.5K
Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
2.5K
Conserved Binding Sites01:49

Conserved Binding Sites

4.2K
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...
4.2K

You might also read

Related Articles

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

Sort by
Same author

SpaTRACE: Spatiotemporal recurrent auto-encoder for reconstructing signaling and regulatory networks from spatiotemporal transcriptomics data.

bioRxiv : the preprint server for biology·2026
Same author

SenSet defines cell-type specific senescence signatures in the aged human lung.

The EMBO journal·2026
Same author

SPRM: spatial process and relationship modeling for multiplexed images.

Bioinformatics advances·2026
Same author

CytoSpatio: Learning cell type spatial relationships using multirange, multitype point process models.

PLoS computational biology·2025
Same author

Big1 is a cell cycle regulator linking cell size to basal body number.

bioRxiv : the preprint server for biology·2025
Same author

Combined Topological Data Analysis and Geometric Deep Learning Reveal Niches by the Quantification of Protein Binding Pockets.

Journal of computational biology : a journal of computational molecular cell biology·2025
Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026
Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026
Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026
Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026
Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026
Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026
See all related articles

Related Experiment Video

Updated: Jun 8, 2025

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
08:38

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

Published on: March 3, 2015

13.3K

Improved protein interaction models predict differences in complexes between human cell lines.

Gary R Wilkins1, Jose Lugo-Martinez1, Robert F Murphy1

  • 1Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University.

Biorxiv : the Preprint Server for Biology
|November 1, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel computational method to predict protein-protein interactions (PPI) strength, improving accuracy and coverage. The approach enhances the mapping of the human protein assembly map by integrating diverse data sources.

Keywords:
cell specificityensemble learningprotein co-expressionprotein complexesprotein localizationprotein-protein interactions

More Related Videos

Author Spotlight: Unraveling the Molecular Mechanisms of Brown and Beige Adipocyte Regulation
07:16

Author Spotlight: Unraveling the Molecular Mechanisms of Brown and Beige Adipocyte Regulation

Published on: January 5, 2024

977
A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

11.1K

Related Experiment Videos

Last Updated: Jun 8, 2025

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
08:38

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells

Published on: March 3, 2015

13.3K
Author Spotlight: Unraveling the Molecular Mechanisms of Brown and Beige Adipocyte Regulation
07:16

Author Spotlight: Unraveling the Molecular Mechanisms of Brown and Beige Adipocyte Regulation

Published on: January 5, 2024

977
A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

11.1K

Area of Science:

  • Computational biology
  • Proteomics
  • Systems biology

Background:

  • Protein-protein interactions (PPI) are fundamental to cellular functions.
  • Experimental PPI data repositories have grown significantly but face limitations like experimental bias and incomplete coverage.
  • Computational approaches are needed to overcome experimental limitations in mapping protein complexes.

Purpose of the Study:

  • To develop a new computational method for predicting the strength of protein interactions.
  • To address limitations of previous PPI prediction methods, specifically incomplete feature sets and proteome coverage.
  • To improve the accuracy and completeness of the human protein assembly map.

Main Methods:

  • Fused data from heterogeneous sources into a feature matrix for protein pairs.
  • Identified minimal feature partitions with complete data for training classifiers.
  • Trained classifiers on feature partitions to predict PPI probabilities and weighted predictions for overall scores.
  • Utilized predicted probabilities with graph-based tools and clustering algorithms for complex assembly.

Main Results:

  • The new method accurately predicts known and probable PPI, outperforming current approaches.
  • Achieved more complete proteome coverage compared to existing PPI prediction methods.
  • Improved results in assembling protein complexes using predicted PPI probabilities.
  • Identified cell-line-specific differences in PPI and complex formation using features from three human cell lines.

Conclusions:

  • The developed computational method offers a significant advancement in predicting protein-protein interaction strength and assembling protein complexes.
  • This approach enhances the comprehensiveness and accuracy of the human protein assembly map.
  • The method has the potential to reveal cell-type-specific protein interaction dynamics.