Enzymatic and structural properties of human glutamine:fructose-6-phosphate amidotransferase 2 (hGFAT2).

Glycoconjugates play a central role in several cellular processes, and alteration in their composition is associated with numerous human pathologies. Substrates for cellular glycosylation are synthesized in the hexosamine biosynthetic pathway, which is controlled by the glutamine:fructose-6-phosphate amidotransfera-se (GFAT). Human isoform 2 GFAT (hGFAT2) has been implicated in diabetes and cancer; however, there is no information about structural and enzymatic properties of this enzyme. Here, we report a successful expression and purification of a catalytically active recombinant hGFAT2 (rhGFAT2) in Escherichia coli cells fused or not to a HisTag at the C-terminal end. Our enzyme kinetics data suggest that hGFAT2 does not follow the expected ordered bi-bi mechanism, and performs the glucosamine-6-phosphate synthesis much more slowly than previously reported for other GFATs. In addition, hGFAT2 is able to isomerize fructose-6-phosphate into glucose-6-phosphate even in the presence of equimolar amounts of glutamine, which results in unproductive glutamine hydrolysis. Structural analysis of a three-dimensional model of rhGFAT2, corroborated by circular dichroism data, indicated the presence of a partially structured loop in the glutaminase domain, whose sequence is present in eukaryotic enzymes but absent in the E. coli homolog. Molecular dynamics simulations suggest that this loop is the most flexible portion of the protein and plays a key role on conformational states of hGFAT2. Thus, our study provides the first comprehensive set of data on the structure, kinetics, and mechanics of hGFAT2, which will certainly contribute to further studies on the (patho)physiology of hGFAT2.

GSAFold: a new application of GSA to protein structure prediction.

The folding process defines three-dimensional protein structures from their amino acid chains. A protein's structure determines its activity and properties; thus knowing such conformation on an atomic level is essential for both basic and applied studies of protein function and dynamics. However, the acquisition of such structures by experimental methods is slow and expensive, and current computational methods mostly depend on previously known structures to determine new ones. Here we present a new software called GSAFold that applies the generalized simulated annealing (GSA) algorithm on ab initio protein structure prediction. The GSA is a stochastic search algorithm employed in energy minimization and used in global optimization problems, especially those that depend on long-range interactions, such as gravity models and conformation optimization of small molecules. This new implementation applies, for the first time in ab initio protein structure prediction, an analytical inverse for the Visitation function of GSA. It also employs the broadly used NAMD Molecular Dynamics package to carry out energy calculations, allowing the user to select different force fields and parameterizations. Moreover, the software also allows the execution of several simulations simultaneously. Applications that depend on protein structures include rational drug design and structure-based protein function prediction. Applying GSAFold in a test peptide, it was possible to predict the structure of mastoparan-X to a root mean square deviation of 3.00 Å.