The Role of a Loop in the Non-catalytic Domain B on the Hydrolysis/Transglycosylation Specificity of the 4-α-Glucanotransferase from Thermotoga maritima.

The mechanism by which glycoside hydrolases control the reaction specificity through hydrolysis or transglycosylation is a key element embedded in their chemical structures. The determinants of reaction specificity seem to be complex. We looked for structural differences in domain B between the 4-α-glucanotransferase from Thermotoga maritima (TmGTase) and the α-amylase from Thermotoga petrophila (TpAmylase) and found a longer loop in the former that extends towards the active site carrying a W residue at its tip. Based on these differences we constructed the variants W131G and the partial deletion of the loop at residues 120-124/128-131, which showed a 11.6 and 11.4-fold increased hydrolysis/transglycosylation (H/T) ratio relative to WT protein, respectively. These variants had a reduction in the maximum velocity of the transglycosylation reaction, while their affinity for maltose as the acceptor was not substantially affected. Molecular dynamics simulations allow us to rationalize the increase in H/T ratio in terms of the flexibility near the active site and the conformations of the catalytic acid residues and their associated pKas.

Modulating Glycoside Hydrolase Activity between Hydrolysis and Transfer Reactions Using an Evolutionary Approach.

The proteins within the CAZy glycoside hydrolase family GH13 catalyze the hydrolysis of polysaccharides such as glycogen and starch. Many of these enzymes also perform transglycosylation in various degrees, ranging from secondary to predominant reactions. Identifying structural determinants associated with GH13 family reaction specificity is key to modifying and designing enzymes with increased specificity towards individual reactions for further applications in industrial, chemical, or biomedical fields. This work proposes a computational approach for decoding the determinant structural composition defining the reaction specificity. This method is based on the conservation of coevolving residues in spatial contacts associated with reaction specificity. To evaluate the algorithm, mutants of α-amylase (TmAmyA) and glucanotransferase (TmGTase) from Thermotoga maritima were constructed to modify the reaction specificity. The K98P/D99A/H222Q variant from TmAmyA doubled the transglycosydation/hydrolysis (T/H) ratio while the M279N variant from TmGTase increased the hydrolysis/transglycosidation ratio five-fold. Molecular dynamic simulations of the variants indicated changes in flexibility that can account for the modified T/H ratio. An essential contribution of the presented computational approach is its capacity to identify residues outside of the active center that affect the reaction specificity.

Selectivity of bacterial proteome fractionation based on differential solubility: a mass spectrometry evaluation.

We investigate the selectivity achieved after differential solubilization of bacterial proteomes following two procedures, both based on successive extraction of proteins in solutions of increasing solubilizing power. Recently, these procedures have gained notable popularity and several commercial kits are now available. A total of 225 proteins in one case and 227 proteins in the other were identified by LC MSMS analysis; 146 of them were identified in both procedures. The proportions of proteins identified as present in only one fraction were 64 and 57%, respectively. The distribution of cytosolic, membrane, and ribosomal proteins among the successive extracts was analyzed in detail. The effect of (1) replacement of low-speed with high-speed centrifugation, (2) omission of detergents in urea solutions, (3) successive washes of pellets, and (4) reproducibility was evaluated. Proteins with positive grand averages of hydropathicity values and membrane proteins were found in all fractions. This study highlights the benefits and limitations of differential solubilization methods, focusing on practical aspects that may strongly influence their selectivity.