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Related Concept Videos

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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Conservation of Protein Domains Over Different Proteins02:26

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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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Statistical inference of protein structural alignments using information and compression.

James H Collier1, Lloyd Allison1, Arthur M Lesk2

  • 1Faculty of Information Technology, Monash University, Clayton, VIC 3800, Australia.

Bioinformatics (Oxford, England)
|January 10, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces MMLigner, a novel computational tool for precise protein structural alignment using a Minimum Message Length (MML) statistical framework. MMLigner reliably infers significant structural alignments and can uncover diverse alignments for complex protein structures.

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Area of Science:

  • Computational structural biology
  • Bioinformatics
  • Statistical modeling

Background:

  • Accurate comparison of protein 3D structures is essential for molecular biology.
  • Existing structural alignment methods lack consistency and reliability.
  • A robust computational framework is needed to address these limitations.

Purpose of the Study:

  • To develop a statistically rigorous framework for inferring precise structural alignments.
  • To implement a computational tool for reliable protein structural alignment.
  • To address the challenge of discovering multiple structural alignments for complex protein structures.

Main Methods:

  • Utilized the Minimum Message Length (MML) principle, a Bayesian and information-theoretic approach.
  • Developed a statistical framework to measure alignment quality based on explanatory power and lossless compression of protein coordinates.
  • Implemented the MMLigner program for inferring statistically significant structural alignments.

Main Results:

  • MMLigner is the first program capable of inferring statistically significant structural alignments.
  • Demonstrated the reliability of MMLigner's results compared to existing state-of-the-art methods.
  • Showcased MMLigner's ability to discover diverse structural alignments of comparable quality, particularly for oligomers and protein complexes.

Conclusions:

  • The MML-based framework provides a consistent and reliable method for structural alignment.
  • MMLigner offers a significant advancement in computational structural biology tools.
  • The software is available for use, facilitating further research in protein structure comparison.