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Protein Organization01:24

Protein Organization

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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.
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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.
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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...
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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.
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A Protocol for Computer-Based Protein Structure and Function Prediction
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Prediction of Protein Structure Using Surface Accessibility Data.

Christoph Hartlmüller1,2, Christoph Göbl1,2, Tobias Madl3,4,5

  • 1Center for Integrated Protein Science Munich, Technische Universität München, Department of Chemistry, Lichtenbergstrasse 4, 85748, Garching, Germany.

Angewandte Chemie (International Ed. in English)
|August 26, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new protein structure prediction method using NMR paramagnetic relaxation enhancements (sPRE) data. Surface accessibility information from sPRE significantly improves the accuracy and speed of protein folding simulations.

Keywords:
CS-RosettaNMR spectroscopyparamagnetic relaxationprotein structure predictionstructural biology

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Computational Biology

Background:

  • Protein structure prediction is crucial for understanding biological function.
  • Current de novo methods face challenges in accuracy and convergence.
  • Nuclear Magnetic Resonance (NMR) techniques offer insights into protein structure.

Purpose of the Study:

  • To develop a novel de novo protein structure prediction approach.
  • To leverage surface accessibility data from sPRE for improved structural modeling.
  • To enhance the accuracy and efficiency of computational protein folding.

Main Methods:

  • Utilized Nuclear Magnetic Resonance (NMR) paramagnetic relaxation enhancements (sPRE) with a soluble paramagnetic compound.
  • Integrated distance-to-surface information from sPRE data into the CS-Rosetta framework.
  • Employed a chemical shift-based computational folding algorithm.

Main Results:

  • Demonstrated that sPRE-derived surface accessibility data accurately reflects protein fold.
  • Showed significant improvements in accuracy and convergence for protein structure prediction.
  • Validated the approach on several protein datasets.

Conclusions:

  • Surface accessibility data from sPRE is a valuable early indicator of correct protein fold.
  • The sPRE-enhanced CS-Rosetta method provides reliable structural models.
  • This approach advances de novo protein structure prediction capabilities.