Computational aspects of thematics: application to protein tyrosine phosphatase role in diabetes mellitus

Abstract

Computation plays an important role in functional genomics and proteomics. Theoretical Microscopic Titration Curves (Thematics) are being employed to predict active binding sites of enzymes. The principal reasons are that the pace of discovery of new proteins is increasing, outpacing the ability to characterize them in conventional biochemical and structural techniques; in addition, advances in computational, structural and force data are used in an interative manner to improve accuracy of active site prediction. From methods using amino acid and nucleotide sequences evidence is available that residues in the enzyme core are selected for stability while those at the surface, which are sites of protein interaction, trade off stability for ligand interactivity. Thematics is a computational method that predicts chemical and electrostatic properties of residues in enzymes and utilizes information contained in those predictions to identify active sites. Discussion of the chemical basis for the predictive powers of Thematics is featured in this paper, and the role of protein tyrosine phosphatase in type 2 diabetes discussed briefly. Key words: Computational aspects, thematics, protein tyrosine phosphatase, diabetes mellitus.