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Protein model representation and construction

M Sullivan1, J Glasgow, E Steeg

  • 1Department of Computing and Information Science, Queen's University, Kingston, Canada. sullivan@qucis.queensu.ca

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|January 1, 1997
PubMed
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This study presents an automated method for protein model construction from crystallographic data, using evolutionary algorithms to speed up structure determination.

Area of Science:

  • Structural biology
  • Computational biology
  • Bioinformatics

Background:

  • Protein structure determination using crystallography is crucial but model construction is complex.
  • Current computational tools require significant expert intervention, making the process time-consuming.

Purpose of the Study:

  • To develop an automated approach for protein model construction from crystallographic data.
  • To reduce the time and expert intervention needed for protein structure determination.

Main Methods:

  • Representing protein models as annotated traces of the 3D backbone.
  • Employing an evolutionary algorithm for potential model generation.
  • Utilizing multiple fitness functions targeting different protein structural levels.

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Main Results:

  • Demonstrated the viability of the automated model construction approach.
  • Preliminary experimental results show promising outcomes.

Conclusions:

  • The developed automated method offers a more efficient way to build protein models from crystallographic data.
  • This approach has the potential to accelerate protein structure determination efforts.