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 Networks02:26

Protein Networks

4.7K
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,...
4.7K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Protein-protein Interfaces02:04

Protein-protein Interfaces

15.0K
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...
15.0K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

4.6K
4.6K
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
Ligand Binding Sites02:40

Ligand Binding Sites

15.7K
Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
15.7K

You might also read

Related Articles

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

Sort by
Same author

IIC-DTI: A Contrastive Learning Enhanced Inter-Intra Molecular Fusing Framework for Drug-Target Interaction Prediction.

Interdisciplinary sciences, computational life sciences·2026
Same author

Graph convolution network based on meta-paths and mutual information for drug-target interaction prediction.

BMC bioinformatics·2025
Same author

The study of the variation of mineral distribution and relative concentration on varieties of oat using synchrotron-based X-ray fluorescence imaging.

Food research international (Ottawa, Ont.)·2025
Same author

Predicting miRNA-Drug Interactions Based on Multi-source Feature Fusion of Heterogeneous Network.

Interdisciplinary sciences, computational life sciences·2025
Same author

Low-Count PET Image Reconstruction With Generalized Sparsity Priors via Unrolled Deep Networks.

IEEE journal of biomedical and health informatics·2025
Same author

DA-HGL: a domain-augmented heterogeneous graph learning framework for protein function prediction.

Briefings in bioinformatics·2025

Related Experiment Video

Updated: Mar 24, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

2.7K

A New Method for Predicting Protein Functions From Dynamic Weighted Interactome Networks.

Bihai Zhao, Jianxin Wang, Min Li

    IEEE Transactions on Nanobioscience
    |March 9, 2016
    PubMed
    Summary

    Predicting protein function computationally is difficult. This study introduces a dynamic weighted interactome network (DWIN) to improve protein function prediction by considering dynamic protein interactions over time.

    More Related Videos

    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

    14.0K
    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
    07:28

    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

    Published on: October 19, 2021

    3.7K

    Related Experiment Videos

    Last Updated: Mar 24, 2026

    Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
    06:50

    Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

    Published on: January 26, 2024

    2.7K
    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

    14.0K
    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
    07:28

    JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

    Published on: October 19, 2021

    3.7K

    Area of Science:

    • Computational biology
    • Bioinformatics
    • Systems biology

    Background:

    • Automated protein function annotation is crucial due to the rapid growth of sequenced genomes.
    • Existing computational methods often overlook the dynamic nature of protein interactions under varying conditions.
    • Protein interactions, abundance, and localization change with cellular conditions and stimuli.

    Purpose of the Study:

    • To develop a novel computational approach for protein function prediction that incorporates dynamic protein interaction information.
    • To address the limitations of static protein-protein interaction (PPI) networks in current function prediction algorithms.

    Main Methods:

    • Constructed a dynamic weighted interactome network (DWIN) by integrating PPI networks with time-course gene expression data.
    • Incorporated protein domain and protein complex information into the DWIN.
    • Developed a prediction method that scores functions based on neighboring proteins in the dynamic network across different time points.

    Main Results:

    • The proposed method effectively predicts protein functions by leveraging dynamic interaction data.
    • Experimental evaluations on PPI datasets showed superior performance compared to existing methods.
    • The DWIN approach successfully captures the temporal dynamics of protein interactions for improved annotation.

    Conclusions:

    • Dynamic protein interactions are critical for accurate protein function prediction.
    • The proposed DWIN-based method offers a significant advancement in computational protein function annotation.
    • This approach enhances our ability to understand protein roles in biological systems under changing conditions.