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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,...
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...
Ligand Binding Sites02:40

Ligand Binding Sites

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...
Protein Organization01:24

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.

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Related Experiment Video

Updated: Jul 5, 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

Protein interaction predictions from diverse sources.

Yin Liu1, Inyoung Kim, Hongyu Zhao

  • 1Department of Neurobiology and Anatomy, University of Texas Medical School at Houston, 6431 Fannin Street, Houston, TX 77030, USA.

Drug Discovery Today
|May 13, 2008
PubMed
Summary
This summary is machine-generated.

Computational methods integrating multiple data sources are crucial for accurate protein-protein interaction mapping. This approach enhances understanding of cellular processes and aids drug target discovery by overcoming experimental limitations.

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

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

Published on: July 6, 2014

Related Experiment Videos

Last Updated: Jul 5, 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

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:

  • Molecular Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Protein-protein interactions are fundamental to cellular functions.
  • Accurate protein interaction data is vital for drug discovery.
  • High-throughput experimental methods generate vast data but have limitations.

Purpose of the Study:

  • To review computational methods for integrating multiple data sources for protein interaction analysis.
  • To highlight strategies for combining direct and indirect interaction information.
  • To leverage diverse genomic and proteomic data for improved accuracy.

Main Methods:

  • Integration of direct protein interaction measurements across diverse organisms.
  • Incorporation of indirect information from genomic and proteomic approaches.
  • Review of computational strategies for data fusion.

Main Results:

  • Computational integration enhances the accuracy of protein-protein interaction networks.
  • Multi-source data fusion overcomes limitations of individual experimental techniques.
  • Improved protein interaction maps facilitate biological pathway analysis.

Conclusions:

  • Computational integration of diverse data is essential for robust protein interaction studies.
  • This approach accelerates the identification of potential drug targets.
  • Future research should focus on refining multi-source data integration techniques.