Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein-protein Interfaces

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 Interfaces

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 Networks

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 Sites

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 Organization

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.

Protein Families

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism. Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members. If these new proteins contain similar amino acids in key locations, protein...

You might also read

Related Articles

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

Sort by

Same author

A systematic evaluation of EEG electrode geometry for enhanced signals: an experimental approach.

Scientific reports·2026

Same author

SynergyGraph: predicting cell line specific drug combination synergy scores using knowledge graph representation and hypergraph modeling.

Scientific reports·2025

Same author

Cognitive load and visual attention assessment using physiological eye tracking measures in multimedia learning.

PloS one·2025

Same author

SynergyImage: image-based model for drug combinations synergy score prediction.

BMC bioinformatics·2025

Same author

Liposomal Cancer Drug Database (LCDD): a comprehensive resource for liposome research in cancer therapy and diagnosis.

Database : the journal of biological databases and curation·2025

Same author

Bridging traditional and deep learning methods in H&E histological image normalization: a comprehensive review and introducing a novel framework for comparative analyses.

Journal of advanced research·2025

Search research articles

Related Experiment Video

Updated: May 10, 2026

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

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

Published on: January 26, 2024

PPIevo: protein-protein interaction prediction from PSSM based evolutionary information.

Javad Zahiri¹, Omid Yaghoubi, Morteza Mohammad-Noori

¹Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.

|June 11, 2013

Summary

A new computational method, PPIevo, predicts protein-protein interactions using evolutionary features from Position-Specific Scoring Matrices. This approach offers improved accuracy and robustness compared to existing sequence-based algorithms.

Keywords:

Computational intelligence Machine learning Position-specific scoring matrix Protein interaction networks Protein–protein interaction map

More Related Videos

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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

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

Published on: March 3, 2015

Related Experiment Videos

Last Updated: May 10, 2026

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

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

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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

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

Published on: March 3, 2015

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Protein-protein interactions (PPIs) are crucial for cellular functions.
Experimental methods for PPI detection have limitations.
Computational approaches are needed to complement experimental techniques.

Purpose of the Study:

To introduce a novel evolutionary-based feature extraction algorithm for PPI prediction.
To develop a method that overcomes limitations of existing sequence-based algorithms.

Main Methods:

Developed PPIevo, an algorithm extracting evolutionary features from Position-Specific Scoring Matrices (PSSM).
The method relies on evolutionary history, independent of protein annotations.
Evaluated performance on the HPRD database.

Main Results:

PPIevo demonstrates superior performance and robustness compared to existing sequence-based methods.
The study highlights the impact of negative dataset selection on performance overestimation.
Evolutionary features extracted by PPIevo enhance prediction power.

Conclusions:

PPIevo offers a powerful and robust approach for predicting protein-protein interactions.
The findings underscore the importance of evolutionary information in PPI prediction.
Caution is advised regarding negative dataset selection to avoid performance overestimation.