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...
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...
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,...

You might also read

Related Articles

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

Sort by
Same author

Towards the construction of a virtual yeast.

Nature·2026
Same author

Disruption of dynactin complex function in intellectual disability.

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

Efficient preservation of old methane-derived organic carbon in deep-sea surface sediments.

Nature communications·2026
Same author

CauFinder: Steering Cell-State and Phenotype Transitions by Causal Disentanglement Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi-Omics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Pioneer: Dynamical Systems Biology for Spatiotemporal Omics Data.

Journal of molecular biology·2026
Same journal

Cumulative Contents.

Biochimica et biophysica acta·2020
Same journal

Molecular Basis of Disease Cumulative Contents.

Biochimica et biophysica acta·2020
Same journal

General Subjects Cumulative Contents.

Biochimica et biophysica acta·2020
Same journal

Erratum to 'on the role of exchangeable hydrogen bonds for the kinetics of P680<sup>+·</sup> Q<sub>A</sub> <sup>-·</sup> formation and P680<sup>+·</sup> Pheo<sup>-·</sup> recombination in photosystem II' [Biochim. Biophys. Acta 1276 (1996) 35-44].

Biochimica et biophysica acta·2019
Same journal

Oligomeric state of the light-harvesting complexes B800-850 and B875 from purple bacterium Rubrivivax gelatinosus in detergent solution.

Biochimica et biophysica acta·2019
Same journal

Regulation of pigment content and enzyme activity in the cyanobacterium Nostoc sp. Mac grown in continuous light, a light-dark photoperiod, or darkness.

Biochimica et biophysica acta·2019
See all related articles

Related Experiment Video

Updated: May 12, 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 sequence-based computational approach to predicting PDZ domain-peptide interactions.

Songyot Nakariyakul1, Zhi-Ping Liu, Luonan Chen

  • 1Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Department of Electrical and Computer Engineering, Thammasat University, Khlong Luang, Pathumthani 12120, Thailand.

Biochimica Et Biophysica Acta
|April 24, 2013
PubMed
Summary
This summary is machine-generated.

Predicting PDZ domain interactions is crucial for understanding diseases. A new computational method accurately identifies PDZ domain-peptide interactions using a reduced set of sequence features, aiding drug discovery.

Keywords:
Dipeptide compositionFeature selectionPDZ domain-peptide interactionProtein interactionProtein sequence encoding

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

Peptide-based Identification of Functional Motifs and their Binding Partners
14:28

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

Related Experiment Videos

Last Updated: May 12, 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

Peptide-based Identification of Functional Motifs and their Binding Partners
14:28

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

Area of Science:

  • Proteomics
  • Computational Biology
  • Structural Biology

Background:

  • PDZ domains are vital protein interaction modules implicated in numerous human diseases.
  • Understanding PDZ domain binding specificity is key to disease mechanism elucidation.
  • Experimental methods for determining PDZ domain interactions are costly and time-consuming.

Purpose of the Study:

  • To develop an accurate and efficient computational method for predicting PDZ domain-peptide interactions.
  • To identify essential sequence features that govern PDZ domain binding specificity.
  • To facilitate drug target identification and design for PDZ domain-related diseases.

Main Methods:

  • Development of a support vector machine (SVM)-based predictor utilizing dipeptide composition.
  • Implementation of a novel hybrid feature selection technique to reduce feature redundancy.
  • Analysis of selected dipeptide features to understand their role in PDZ domain specificity.

Main Results:

  • The SVM predictor achieved high accuracy in qualitatively predicting PDZ domain-peptide interactions.
  • The hybrid feature selection method identified a concise subset (approx. 25%) of dipeptide features.
  • The proposed method significantly improved prediction performance compared to using all features.

Conclusions:

  • A computationally efficient method based on primary sequence information can accurately predict PDZ domain-peptide interactions.
  • Selected dipeptide features offer insights into PDZ domain specificity patterns.
  • This approach supports drug discovery efforts by identifying potential PDZ domain-ligand interactions.