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Predicting substrates by docking high-energy intermediates to enzyme structures.

Johannes C Hermann1, Eman Ghanem, Yingchun Li

  • 1Department of Pharmaceutical Chemistry, University of California, San Francisco, MC 2550, San Francisco, California 94158-2330, USA.

Journal of the American Chemical Society
|December 7, 2006
PubMed
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Predicting enzyme activity is crucial. This study shows docking high-energy intermediates accurately predicts enzyme substrates and stereoselectivity, outperforming standard methods.

Area of Science:

  • Biochemistry
  • Structural Biology
  • Computational Chemistry

Background:

  • Determining enzyme function from protein structure is a growing challenge.
  • Structure-based prediction of enzyme activity requires accurate substrate identification.

Purpose of the Study:

  • To develop and validate a method for predicting enzyme substrates and activity using structure-based docking.
  • To assess the efficacy of docking high-energy intermediate forms of substrates compared to ground-state forms.

Main Methods:

  • Created a database of high-energy transition-state analogues from KEGG metabolites.
  • Docked metabolites in both ground-state and high-energy intermediate forms into amidohydrolase enzymes.
  • Tested prospective prediction of enantioselectivity for phosphotriesterase using chiral substrates.

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Main Results:

  • Docking high-energy intermediates significantly improved substrate discrimination over ground-state docking.
  • The method correctly predicted stereoselectivity for 18 out of 20 substrate/enzyme combinations.
  • Significant differences in stereoselectivity ratios and switches were observed and accurately predicted.

Conclusions:

  • Docking high-energy intermediates is a robust method for predicting enzyme substrates and activity.
  • This approach enhances the accuracy of structure-based enzyme function prediction.
  • The method shows promise for application to a wider range of enzymes.