Rational pH-engineering of the thermostable xylanase based on computational model

Living in trinity of extremes: Genomic and proteomic signatures of halophilic, thermophilic, and pH adaptation

Since nucleic acids and proteins of unicellular prokaryotes are directly exposed to extreme environmental conditions, it is possible to explore the genomic-proteomic compositional determinants of molecular mechanisms of adaptation developed by them in response to harsh environmental conditions. Using a wealth of currently available complete genomes/proteomes we were able to explore signatures of adaptation to three environmental factors, pH, salinity, and temperature, observing major trends in compositions of their nucleic acids and proteins. We derived predictors of thermostability, halophilic, and pH adaptations and complemented them by the principal components analysis. We observed a clear difference between thermophilic and salinity/pH adaptations, whereas latter invoke seemingly overlapping mechanisms. The genome-proteome compositional trade-off reveals an intricate balance between the work of base paring and base stacking in stabilization of coding DNA and r/tRNAs, and, at the same time, universal requirements for the stability and foldability of proteins regardless of the nucleotide biases. Nevertheless, we still found hidden fingerprints of ancient evolutionary connections between the nucleotide and amino acid compositions indicating their emergence, mutual evolution, and adjustment. The evolutionary perspective on the adaptation mechanisms is further studied here by means of the comparative analysis of genomic/proteomic traits of archaeal and bacterial species. The overall picture of genomic/proteomic signals of adaptation obtained here provides a foundation for future engineering and design of functional biomolecules resistant to harsh environments.

Three Molecular Modification Strategies to Improve the Thermostability of Xylanase XynA from Streptomyces rameus L2001

Glycoside hydrolase family 11 (GH11) xylanases are the preferred candidates for the production of functional oligosaccharides. However, the low thermostability of natural GH11 xylanases limits their industrial applications. In this study, we investigated the following three strategies to modify the thermostability of xylanase XynA from Streptomyces rameus L2001 mutation to reduce surface entropy, intramolecular disulfide bond construction, and molecular cyclization. Changes in the thermostability of XynA mutants were analyzed using molecular simulations. All mutants showed improved thermostability and catalytic efficiency compared with XynA, except for molecular cyclization. The residual activities of high-entropy amino acid-replacement mutants Q24A and K104A increased from 18.70% to more than 41.23% when kept at 65 °C for 30 min. The catalytic efficiencies of Q24A and K143A increased to 129.99 and 92.26 mL/s/mg, respectively, compared with XynA (62.97 mL/s/mg) when using beechwood xylan as the substrate. The mutant enzyme with disulfide bonds formed between Val3 and Thr30 increased the t_1/2^{60 °C} by 13.33-fold and the catalytic efficiency by 1.80-fold compared with the wild-type XynA. The high thermostabilities and hydrolytic activities of XynA mutants will be useful for enzymatic production of functional xylo-oligosaccharides.

Robust enzyme design: bioinformatic tools for improved protein stability

The ability of proteins and enzymes to maintain a functionally active conformation under adverse environmental conditions is an important feature of biocatalysts, vaccines, and biopharmaceutical proteins. From an evolutionary perspective, robust stability of proteins improves their biological fitness and allows for further optimization. Viewed from an industrial perspective, enzyme stability is crucial for the practical application of enzymes under the required reaction conditions. In this review, we analyze bioinformatic-driven strategies that are used to predict structural changes that can be applied to wild type proteins in order to produce more stable variants. The most commonly employed techniques can be classified into stochastic approaches, empirical or systematic rational design strategies, and design of chimeric proteins. We conclude that bioinformatic analysis can be efficiently used to study large protein superfamilies systematically as well as to predict particular structural changes which increase enzyme stability. Evolution has created a diversity of protein properties that are encoded in genomic sequences and structural data. Bioinformatics has the power to uncover this evolutionary code and provide a reproducible selection of hotspots - key residues to be mutated in order to produce more stable and functionally diverse proteins and enzymes. Further development of systematic bioinformatic procedures is needed to organize and analyze sequences and structures of proteins within large superfamilies and to link them to function, as well as to provide knowledge-based predictions for experimental evaluation.

Computational design of a pH stable enzyme: understanding molecular mechanism of penicillin acylase's adaptation to alkaline conditions

Protein stability provides advantageous development of novel properties and can be crucial in affording tolerance to mutations that introduce functionally preferential phenotypes. Consequently, understanding the determining factors for protein stability is important for the study of structure-function relationship and design of novel protein functions. Thermal stability has been extensively studied in connection with practical application of biocatalysts. However, little work has been done to explore the mechanism of pH-dependent inactivation. In this study, bioinformatic analysis of the Ntn-hydrolase superfamily was performed to identify functionally important subfamily-specific positions in protein structures. Furthermore, the involvement of these positions in pH-induced inactivation was studied. The conformational mobility of penicillin acylase in Escherichia coli was analyzed through molecular modeling in neutral and alkaline conditions. Two functionally important subfamily-specific residues, Gluβ482 and Aspβ484, were found. Ionization of these residues at alkaline pH promoted the collapse of a buried network of stabilizing interactions that consequently disrupted the functional protein conformation. The subfamily-specific position Aspβ484 was selected as a hotspot for mutation to engineer enzyme variant tolerant to alkaline medium. The corresponding Dβ484N mutant was produced and showed 9-fold increase in stability at alkaline conditions. Bioinformatic analysis of subfamily-specific positions can be further explored to study mechanisms of protein inactivation and to design more stable variants for the engineering of homologous Ntn-hydrolases with improved catalytic properties.

Tailoring the pH dependence of human non-pancreatic secretory phospholipase A2 by engineering surface charges

Human non-pancreatic secretory phospholipase A2 (hnpsPLA2) catalyzes the sn-2 acyl hydrolysis of phospholipids. It was reported that hnpsPLA2 is involved in various diseases like inflammation, cancer, and so on. This enzyme also exhibits anti-bacterial and anti-virus activities. It is active over a broad pH range, with higher activity at alkaline conditions. In order to make it suitable as a potential bactericide, high activity at neutral pH is preferable. We have tried to tailor the pH dependence of hnpsPLA2 activity by replacing its surface charged residues. Three surface charge replacements, Arg42Glu, Arg100Glu, and Glu89Lys, showed increased activities at neutral pH, which are 2.3, 2.8, and 2.3 times that of the wild-type enzyme at pH 7. Both the positive-to-negative and negative-to-positive mutations lowered the optimum enzymatic reaction pH of hnpsPLA2, indicating that the enzyme pH profile depends on a delicate balance of charged residues. The activity changes are in good agreement with the recently proposed calcium-coordinated catalytic triad mechanism. This study also provides a general means of enhancing hnpsPLA2 activity at low pH.

Alkalophilic adaptation of XynB endoxylanase from Aspergillus niger via rational design of pKa of catalytic residues

Based on the strategy of changing pH-stability profiles by altering pKa values of catalytic residues, rational protein engineering was applied to improve alkalophilic adaptation of Aspergillus niger endoxylanase XynB. Computational predictions and molecular modeling were carried out using PROPKA server and SWISS-MODEL server, respectively. Three endoxylanase mutant of S108V, N151E, and Q178R, in which the pKa values of either catalytic glutamate residues shifted, were generated. In agreement with expectation, the variant of Q178R improved alkalophilic performances. The mutant Q178R raised the optimum pH of XynB from 5.5 to 6.0 and retained 37% of the maximum activity at pH 8.0. Interestingly, the pKa values of Glu84 and Glu175 in Q178R are 7.91 and 6.32, respectively. The pKa of Glu175 is lower than that of Glu84, as opposed to the fact that the pKa of Glu84 is lower than that of Glu175 in other GH11 xylanases. It indicated that Glu175 may convert into a nucleophile residue and Glu84 into an acid/base residue.