Electrostatic interaction optimization improves catalytic rates and thermotolerance on xylanases.

Understanding the aspects that contribute to improving proteins' biochemical properties is of high relevance for protein engineering. Properties such as the catalytic rate, thermal stability, and thermal resistance are crucial for applying enzymes in the industry. Different interactions can influence those biochemical properties of an enzyme. Among them, the surface charge-charge interactions have been a target of particular attention. In this study, we employ the Tanford-Kirkwood solvent accessibility model using the Monte Carlo algorithm (TKSA-MC) to predict possible interactions that could improve stability and catalytic rate of a WT xylanase (XynAWT) and its M6 xylanase (XynAM6) mutant. The modeling prediction indicates that mutating from a lysine in position 99 to a glutamic acid (K99E) favors the native state stabilization in both xylanases. Our lab results showed that mutated xylanases had their thermotolerance and catalytic rate increased, which conferred higher processivity of delignified sugarcane bagasse. The TKSA-MC approach employed here is presented as an efficient computational-based design strategy that can be applied to improve the thermal resistance of enzymes with industrial and biotechnological applications.

The Role of Electrostatics and Folding Kinetics on the Thermostability of Homologous Cold Shock Proteins.

Understanding which aspects contribute to the thermostability of proteins is a challenge that has persisted for decades, and it is of great relevance for protein engineering. Several types of interactions can influence the thermostability of a protein. Among them, the electrostatic interactions have been a target of particular attention. Aiming to explore how this type of interaction can affect protein thermostability, this paper investigated four homologous cold shock proteins from psychrophilic, mesophilic, thermophilic, and hyperthermophilic organisms using a set of theoretical methodologies. It is well-known that electrostatics as well as hydrophobicity are key-elements for the stabilization of these proteins. Therefore, both interactions were initially analyzed in the native structure of each protein. Electrostatic interactions present in the native structures were calculated with the Tanford-Kirkwood model with solvent accessibility, and the amount of hydrophobic surface area buried upon folding was estimated by measuring both folded and extended structures. On the basis of Energy Landscape Theory, the local frustration and the simplified alpha-carbon structure-based model were modeled with a Debye-Hückel potential to take into account the electrostatics and the effects of an implicit solvent. Thermodynamic data for the structure-based model simulations were collected and analyzed using the Weighted Histogram Analysis and Stochastic Diffusion methods. Kinetic quantities including folding times, transition path times, folding routes, and Φ values were also obtained. As a result, we found that the methods are able to qualitatively infer that electrostatic interactions play an important role on the stabilization of the most stable thermophilic cold shock proteins, showing agreement with the experimental data.