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Ion Mobility-Mass Spectrometry Techniques for Determining the Structure and Mechanisms of Metal Ion Recognition and Redox Activity of Metal Binding Oligopeptides
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PM3-compatible zinc parameters optimized for metalloenzyme active sites.

Edward N Brothers1, Dimas Suarez, David W Deerfield

  • 1Department of Chemistry, 152 Davey Laboratory, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.

Journal of Computational Chemistry
|September 14, 2004
PubMed
Summary

New ZnB parameters improve modeling of zinc metalloenzymes, reducing average errors in heat of formation calculations from 46.9 to 14.2 kcal/mol. This enhances accuracy for biological zinc compounds.

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Characterizing Mammalian Zinc Transporters Using an In Vitro Zinc Transport Assay

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Area of Science:

  • Computational Chemistry
  • Biochemistry
  • Quantum Chemistry

Background:

  • Semiempirical methods (PM3, AM1) show unreliability for zinc compounds in biological contexts.
  • Existing models fail to accurately predict geometries of zinc metalloenzyme active sites.

Purpose of the Study:

  • To reparameterize zinc at the PM3 level for improved accuracy in modeling zinc metalloenzymes.
  • To develop a new parameter set (ZnB) for enhanced structural and energetic predictions.

Main Methods:

  • Incorporation of frequency-corrected B3LYP/6-311G* zinc metalloenzyme ligand environments.
  • Inclusion of experimental data for parameter refinement.
  • Development of the ZnB parameter set for zinc.

Main Results:

  • Reduced average errors in heat of formation from 46.9 kcal/mol (PM3) to 14.2 kcal/mol with ZnB.
  • ZnB parameter set accurately predicts geometries for Bacillus fragilis active site models and other zinc metalloenzyme mimics.
  • Qualitative agreement with high-level ab initio results achieved.

Conclusions:

  • The ZnB parameter set significantly improves the reliability of semiempirical methods for zinc-containing biological compounds.
  • Accurate geometric predictions are crucial for understanding zinc metalloenzyme function.
  • ZnB offers a more dependable computational tool for studying zinc metalloenzymes.