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Using structural motif templates to identify proteins with DNA binding function.

Susan Jones1, Jonathan A Barker, Irene Nobeli

  • 1EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. suej@ebi.ac.uk

Nucleic Acids Research
|May 29, 2003
PubMed
Summary
This summary is machine-generated.

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This study presents a method to predict DNA binding function from protein structure using 3D templates. It accurately identifies helix-turn-helix (HTH) motifs, crucial for DNA binding, in proteins.

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • DNA-binding proteins are essential in cellular processes.
  • Helix-turn-helix (HTH) motifs are common DNA-binding structures.
  • Predicting DNA-binding function from protein structure is challenging.

Purpose of the Study:

  • To develop and validate a computational method for predicting DNA-binding function based on protein structure.
  • To identify proteins containing helix-turn-helix (HTH) motifs.

Main Methods:

  • Created a structural template library of seven HTH motifs from non-homologous DNA-binding proteins.
  • Developed an algorithm to scan protein structures using templates and calculate root mean squared deviation (rmsd).
  • Established threshold values for rmsd and accessible surface area to distinguish HTH-containing proteins.

Related Experiment Videos

Main Results:

  • A threshold of 1.6 Å rmsd achieved an 88.4% true hit rate and 0.7% false positive rate.
  • Further refinement using an accessible surface area threshold of 990 Ų reduced the false positive rate to 0.5%.
  • The method was successfully applied to predict DNA-binding function in target proteins from a structural genomics project.

Conclusions:

  • The developed method provides a reliable way to predict DNA-binding function from protein structure.
  • The HTH motif template library and validated thresholds are effective for identifying DNA-binding proteins.
  • This approach has implications for structural genomics and understanding protein function.