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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,...
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,...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

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 to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

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 to...

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Related Experiment Video

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Identifying Protein-protein Interaction Sites Using Peptide Arrays
07:44

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Published on: November 18, 2014

Strike: a protein-protein interaction classification approach.

Nazar Zaki1, Wassim El-Hajj, Hesham M Kamel

  • 1Bioinformatics Laboratory, Department of Intelligent Systems, College of Information Technology, UAE University, 17551, Al-Ain, UAE. nzaki@uaeu.ac.ae

Advances in Experimental Medicine and Biology
|March 25, 2011
PubMed
Summary
This summary is machine-generated.

We developed STRIKE, a novel method using String Kernel to predict protein-protein interactions based on amino acid sequences. STRIKE shows improved performance in identifying interacting and non-interacting protein pairs.

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Last Updated: Jun 3, 2026

Identifying Protein-protein Interaction Sites Using Peptide Arrays
07:44

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Published on: November 18, 2014

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

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics
12:53

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

Published on: July 6, 2014

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Protein-protein interactions (PPIs) are fundamental to cellular function and biological processes.
  • Understanding PPIs is crucial for deciphering cellular mechanisms and identifying potential therapeutic targets.
  • Existing methods for PPI prediction often require complex experimental data or structural information.

Purpose of the Study:

  • To introduce STRIKE, a novel computational approach for predicting protein-protein interactions.
  • To leverage amino acid sequence information for classifying protein pairs as interacting or non-interacting.
  • To evaluate the efficacy of the String Kernel method for PPI prediction.

Main Methods:

  • The STRIKE approach utilizes the String Kernel method for classification.
  • It analyzes amino acid sequences to identify similar substrings between protein pairs.
  • The method classifies proteins as interacting if they share significant sequence similarities, inferring potential homology and structural relationships.

Main Results:

  • STRIKE successfully classifies protein pairs into interacting and non-interacting sets based solely on sequence data.
  • The String Kernel approach demonstrated effectiveness in protein sequence classification.
  • STRIKE achieved reasonable improvements compared to existing PPI prediction methods on a yeast protein interaction dataset.

Conclusions:

  • STRIKE offers a novel and effective sequence-based method for predicting protein-protein interactions.
  • The String Kernel approach is a viable tool for analyzing protein sequences and predicting functional relationships.
  • This method provides a valuable contribution to the field of computational biology for PPI research.