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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 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.
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...

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Related Experiment Video

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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

Struct2Net: a web service to predict protein-protein interactions using a structure-based approach.

Rohit Singh1, Daniel Park, Jinbo Xu

  • 1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.

Nucleic Acids Research
|June 2, 2010
PubMed
Summary
This summary is machine-generated.

Struct2Net predicts protein-protein interactions (PPIs) using a novel structure-based method, independent of genomic data. This resource offers flexible querying and rapid predictions for common organisms, aiding drug design and experimental planning.

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

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Experimental determination of protein-protein interactions (PPIs) is crucial for understanding cellular mechanisms but remains experimentally incomplete.
  • Existing computational resources for PPI prediction often rely on functional genomic data, limiting their scope and applicability.
  • A structure-based approach offers an alternative, independent method for predicting PPIs.

Purpose of the Study:

  • To introduce Struct2Net, a novel web server for predicting protein-protein interactions (PPIs) using a structure-based computational approach.
  • To provide a community resource for PPI prediction that surpasses homology modeling and functional genomic data dependencies.
  • To offer a flexible and accessible platform for researchers to explore potential PPIs.

Main Methods:

  • Struct2Net employs a structure-based computational strategy for predicting interactions between arbitrary protein pairs.
  • The method requires only the amino acid sequence information of the queried proteins, making it broadly applicable.
  • The web server provides pre-computed predictions for commonly studied organisms (fly, human, yeast) and options for orthology-based or direct computation for other species.

Main Results:

  • Struct2Net is presented as the first community resource offering structure-based PPI predictions beyond homology modeling.
  • The platform allows for flexible querying, including rapid retrieval of pre-computed results for major model organisms.
  • Users can obtain approximate or full computational predictions for proteins from diverse species.

Conclusions:

  • Struct2Net provides a valuable, structure-independent resource for predicting protein-protein interactions, complementing existing methods.
  • The web server's flexibility and speed enhance its utility for researchers in various biological disciplines.
  • This tool has the potential to accelerate experimental design and drug discovery by identifying novel protein interaction partners.