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A comparison of X-ray and calculated structures of the enzyme MTH1
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. University of Colorado, USA.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
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Number of Authors: 5
2016 (English)In: Journal of Molecular Modeling, ISSN 1610-2940, E-ISSN 0948-5023, Vol. 22, no 7, 168Article in journal (Refereed) Published
Abstract [en]

Modern computational chemistry methods provide a powerful tool for use in refining the geometry of proteins determined by X-ray crystallography. Specifically, computational methods can be used to correctly place hydrogen atoms unresolved by this experimental method and improve bond geometry accuracy. Using the semiempirical method PM7, the structure of the nucleotide-sanitizing enzyme MTH1, complete with hydrolyzed substrate 8-oxo-dGMP, was optimized and the resulting geometry compared with the original X-ray structure of MTH1. After determining hydrogen atom placement and the identification of ionized sites, the charge distribution in the binding site was explored. Where comparison was possible, all the theoretical predictions were in good agreement with experimental observations. However, when these were combined with additional predictions for which experimental observations were not available, the result was a new and alternative description of the substrate-binding site interaction. An estimate was made of the strengths and weaknesses of the PM7 method for modeling proteins on varying scales, ranging from overall structure to individual interatomic distances. An attempt to correct a known fault in PM7, the under-estimation of steric repulsion, is also described. This work sheds light on the specificity of the enzyme MTH1 toward the substrate 8-oxo-dGTP; information that would facilitate drug development involving MTH1.

Place, publisher, year, edition, pages
2016. Vol. 22, no 7, 168
Keyword [en]
Binding site, Enzyme, MTH1, Nudix box, 8-oxo-dGMP, PM7, Salt bridges
National Category
Biological Sciences Chemical Sciences Computer and Information Science
URN: urn:nbn:se:su:diva-132550DOI: 10.1007/s00894-016-3025-xISI: 000379014700023PubMedID: 27350386OAI: diva2:955291
Available from: 2016-08-25 Created: 2016-08-15 Last updated: 2016-08-25Bibliographically approved

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