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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,...
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 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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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

Deep architectures for protein contact map prediction.

Pietro Di Lena1, Ken Nagata, Pierre Baldi

  • 1Department of Computer Science, University of California, Irvine, CA 92697, USA.

Bioinformatics (Oxford, England)
|August 1, 2012
PubMed
Summary
This summary is machine-generated.

We developed CMAPpro, a new machine learning method for protein contact map prediction. This approach significantly improves the accuracy of predicting long-range contacts, crucial for protein structure prediction.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

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09:51

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Machine learning in proteomics

Background:

  • Accurate residue-residue contact prediction is vital for protein structure prediction.
  • Current methods struggle with long-range contacts, limiting ab initio structure prediction.
  • Existing contact predictors achieve less than 20% accuracy for long-range contacts.

Purpose of the Study:

  • To develop a novel machine learning approach for enhanced protein contact map prediction.
  • To significantly improve the accuracy of predicting long-range residue-residue contacts.
  • To provide a tool that aids in accurate protein structure prediction.

Main Methods:

  • A three-step approach integrating 2D recursive neural networks and an energy-based method.
  • Utilizing a deep neural network architecture for progressive refinement of contact predictions.
  • Training on a large, non-redundant protein dataset and testing on non-homologous domains and CASP datasets.

Main Results:

  • The novel CMAPpro predictor achieves close to 30% accuracy for long-range contacts.
  • This represents a significant improvement over existing protein contact prediction methods.
  • The method integrates information across space and time for refined predictions.

Conclusions:

  • CMAPpro offers a substantial advancement in protein contact map prediction accuracy.
  • The improved prediction of long-range contacts is critical for accurate ab initio protein structure prediction.
  • CMAPpro is available as part of the SCRATCH suite for broader accessibility.