Modulator of Diabetes and Metabolic Syndrome: Silent Proteins, newer Insights

Computational methods 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 iterative 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. In THEMATICS method the underlying concept is that active site residues involved in specific biochemical actions have predictable chemical properties which are identified using pH titrations of the enzyme activity. A more recent method uses a more comprehensive physico-chemical and electrical interaction map of amino acids at the surface of the protein which are likely to be sites of interactions with other proteins and chemicals. In summary, computational tools offer simulation and analytical opportunities to characterize, identify and modify proteins with appropriate characteristics to catalyze the specific biochemical reaction that is required. In this review the enzyme butyrylcholinesterase, involved in the expression of metabolic syndrome is presented, and recently available methods to predict protein structure, function and active sites are summarized.