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Protein and Protein Structure02:15

Protein and Protein Structure

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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
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Multi-criteria protein structure comparison and structural similarities analysis using pyMCPSC.

Anuj Sharma1, Elias S Manolakos1,2

  • 1Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens, Greece.

Plos One
|October 18, 2018
PubMed
Summary
This summary is machine-generated.

pyMCPSC is a new Python tool for efficient Multi-Criteria Protein Structure Comparison (MCPSC). It uses multi-core CPUs to analyze protein domain similarities and aid in structural biology and drug discovery.

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Area of Science:

  • Computational proteomics
  • Structural biology
  • Bioinformatics

Background:

  • Protein Structure Comparison (PSC) is crucial in structural biology and drug discovery.
  • The emergence of new PSC methods necessitates consensus scoring through Multi-Criteria Protein Structure Comparison (MCPSC).

Purpose of the Study:

  • To introduce pyMCPSC, a Python utility for efficient MCPSC.
  • To enable users to perform MCPSC by leveraging multi-core CPU parallelism.

Main Methods:

  • Developed pyMCPSC, a Python-based utility for MCPSC.
  • Utilized multi-core CPU parallelism for efficient computation.
  • Applied pyMCPSC to analyze protein domain similarities in the Proteus_300 dataset.

Main Results:

  • pyMCPSC scores reliably identify protein domain classifications, confirmed by ROC and Nearest-Neighbor analyses.
  • Generated structure similarity-based Phylogenetic Trees offer insights into functional grouping.
  • Scatter plots revealed strong correlations within SCOP Class C and loose correlations within SCOP Class D protein domains.

Conclusions:

  • pyMCPSC facilitates efficient MCPSC and analysis of protein domain datasets.
  • The tool aids in gaining rapid insights through visualizations like Phylogenetic Trees and scatter plots.
  • pyMCPSC is extensible for incorporating new PSC methods and is available under GPLv3.0 license.