Literature DB >> 16399353

A comparative molecular field analysis-based approach to prediction of sulfotransferase catalytic specificity.

Vyas Sharma1, Michael W Duffel.   

Abstract

Understanding the catalytic function and substrate specificity of cytosolic sulfotransferases (SULTs) involved in drug metabolism is essential for predicting the metabolic outcomes of many xenobiotics. Although multiple isoforms of cytosolic SULTs have been identified and characterized in humans and other species, relatively little is known about the specific molecular interactions that govern their selectivity for substrates. The use of three-dimensional quantitative structure-activity relationship (3D-QSAR) techniques has emerged as a powerful tool for understanding the relationships among protein structure, catalytic function, and substrate specificity. We have found that a specific adaptation of a ligand-based 3D-QSAR method, comparative molecular field analysis (CoMFA), is particularly useful for prediction of the catalytic efficiencies of SULTs. This approach has been used to study the function of a prototypical rat hepatic phenol SULT and has now been extended to a member of the hydroxysteroid SULT family. Key aspects of this methodology incorporate strategies for finding the most meaningful bioactive conformation with respect to the protein structure, use of a model of an enzyme-substrate complex incorporating the mechanism of sulfuryl transfer, and the utilization of log(k(cat)/K(m)) as the parameter for correlation analysis. The success of this approach with members of two different families of cytosolic SULTs suggests that it may be of more general use in the study of other SULTs.

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Year:  2005        PMID: 16399353     DOI: 10.1016/S0076-6879(05)00014-5

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  2 in total

1.  Accurate prediction of glucuronidation of structurally diverse phenolics by human UGT1A9 using combined experimental and in silico approaches.

Authors:  Baojian Wu; Xiaoqiang Wang; Shuxing Zhang; Ming Hu
Journal:  Pharm Res       Date:  2012-06       Impact factor: 4.200

2.  In silico mechanistic profiling to probe small molecule binding to sulfotransferases.

Authors:  Virginie Y Martiny; Pablo Carbonell; David Lagorce; Bruno O Villoutreix; Gautier Moroy; Maria A Miteva
Journal:  PLoS One       Date:  2013-09-06       Impact factor: 3.240

  2 in total

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