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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.
The primary structure of a protein is its amino acid sequence....
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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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Many proteins can be classified into two distinct subtypes - globular or fibrous. These two types differ in their shapes and solubilities.
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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.
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Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering
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Data Mining of Macromolecular Structures.

Bart van Beusekom1, Anastassis Perrakis1, Robbie P Joosten2

  • 1Department of Biochemistry, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.

Methods in Molecular Biology (Clifton, N.J.)
|April 27, 2016
PubMed
Summary
This summary is machine-generated.

Selecting high-quality macromolecular structures from the Protein Data Bank (PDB) is crucial for data mining. This chapter guides users on choosing optimal protein models by addressing data uniformity and quality issues in PDB entries.

Keywords:
AnnotationData miningPDBPDB_REDOStandardizationUniformityValidation

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Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Chemistry

Background:

  • Macromolecular structures are vital for diverse applications, including drug development and education.
  • The Protein Data Bank (PDB) is the primary repository for experimentally determined macromolecular structures.
  • Selecting appropriate PDB data for analysis and data mining is challenging due to variations in quality and standardization.

Purpose of the Study:

  • To explain challenges in data standardization, annotation, and uniformity for X-ray crystallography-derived PDB entries.
  • To discuss the impact of crystallographic data quality and model optimization on structural models.
  • To provide guidelines for selecting suitable protein structure models for detailed analysis and data mining.

Main Methods:

  • Analysis of data standardization and uniformity issues in PDB entries.
  • Evaluation of crystallographic data quality and model optimization effects.
  • Discussion of validation tools for informed model selection.
  • Exploration of the PDB_REDO databank as a supplementary resource.

Main Results:

  • Identified challenges in PDB data uniformity and standardization, particularly for X-ray crystallography.
  • Highlighted the influence of data quality and refinement methods on structural model accuracy.
  • Demonstrated the utility of validation tools in assessing and selecting appropriate structural models.

Conclusions:

  • Informed selection of protein structure models requires understanding data quality and validation metrics.
  • The PDB_REDO databank offers advantages for accessing improved structural data.
  • Guidelines are provided to facilitate the selection of optimal PDB models for data mining and analysis.