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Related Concept Videos

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.
Protein Organization01:13

Protein Organization

Overview
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.
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 Folding01:22

Protein Folding

Overview
Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Extracting knowledge from protein structure geometry.

Peter Røgen1, Patrice Koehl

  • 1Department of Mathematics, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark. Peter.Roegen@mat.dtu.dk

Proteins
|January 3, 2013
PubMed
Summary

This study introduces the Metric Protein Potential (MPP), a novel computational method that improves protein structure prediction. MPP accurately identifies native protein structures by correlating model energy with structural accuracy, outperforming existing methods.

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Biophysics

Background:

  • Protein structure prediction is crucial for understanding protein function.
  • Current methods struggle to accurately distinguish native protein structures from misfolded ones.
  • Existing force fields often fail to identify native states due to complexities in free energy landscapes.

Purpose of the Study:

  • To develop a new potential, Metric Protein Potential (MPP), for enhanced protein structure evaluation.
  • To improve the accuracy of identifying native-like protein models from generated decoys.
  • To address limitations of current force fields in protein structure assessment.

Main Methods:

  • Derived a novel potential (MPP) using geometric information from native and misfolded protein conformers.
  • Incorporated local (7-mer fragment mapping) and nonlocal (residue-based pairwise, solvent) geometric features.
  • Optimized MPP to maximize correlation between structural model energy and root mean square deviation (RMSD) to the native structure.

Main Results:

  • MPP demonstrated a strong correlation between predicted energy and RMSD to native structures.
  • The new potential successfully retrieved native protein structures from sets of high-resolution decoys.
  • MPP's composite nature, integrating local and nonlocal information, proved effective.

Conclusions:

  • Metric Protein Potential (MPP) offers a significant advancement in evaluating protein structural models.
  • MPP's ability to correlate energy with RMSD enhances the identification of native protein conformations.
  • This approach provides a more reliable method for protein structure prediction and analysis.