Effect of acidic amino acids engineered into the active site cleft ofThermopolyspora flexuosaGH11 xylanase

Navigating the landscape of enzyme design: from molecular simulations to machine learning

Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is challenging to navigate the vast sequence space to identify those proteins with admirable biocatalytic functions. The recent development of deep-learning based structure prediction methods such as AlphaFold2 reinforced by different computational simulations or multiscale calculations has largely expanded the 3D structure databases and enabled structure-based design. While structure-based approaches shed light on site-specific enzyme engineering, they are not suitable for large-scale screening of potential biocatalysts. Effective utilization of big data using machine learning techniques opens up a new era for accelerated predictions. Here, we review the approaches and applications of structure-based and machine-learning guided enzyme design. We also provide our view on the challenges and perspectives on effectively employing enzyme design approaches integrating traditional molecular simulations and machine learning, and the importance of database construction and algorithm development in attaining predictive ML models to explore the sequence fitness landscape for the design of admirable biocatalysts.

Molecular modification and biotechnological applications of microbial aspartic proteases

The growing preference for incorporating microbial aspartic proteases in industries is due to their high catalytic function and high degree of substrate selectivity. These properties, however, are attributable to molecular alterations in their structure and a variety of other characteristics. Molecular tools, functional genomics, and genome editing technologies coupled with other biotechnological approaches have aided in improving the potential of industrially important microbial proteases by addressing some of their major limitations, such as: low catalytic efficiency, low conversion rates, low thermostability, and less enzyme yield. However, the native folding within their full domain is dependent on a surrounding structure which challenges their functionality in substrate conversion, mainly due to their mutual interactions in the context of complex systems. Hence, manipulating their structure and controlling their expression systems could potentially produce enzymes with high selectivity and catalytic functions. The proteins produced by microbial aspartic proteases are industrially capable and far-reaching in regulating certain harmful distinctive industrial processes and the benefits of being eco-friendly. This review provides: an update on current trends and gaps in microbial protease biotechnology, exploring the relevant recombinant strategies and molecular technologies widely used in expression platforms for engineering microbial aspartic proteases, as well as their potential industrial and biotechnological applications.

Whole-genome sequence and mass spectrometry study of the snow blight fungus Phacidium infestans (Karsten) DSM 5139 growing at freezing temperatures

Phacidium infestans (synonym Gremmenia infestans) is a significant pathogen that impacts Pinus species across the northern regions of Europe and Asia. This study introduces the genome sequence of P. infestans Karsten DSM 5139 (Phain), obtained through Pacbio technology. The assembly resulted in 44 contigs, with a total genome size of 36,805,277 bp and a Guanine-Cytosine content of 46.4%. Genome-mining revealed numerous putative biosynthetic gene clusters that code for virulence factors and fungal toxins. The presence of the enzyme pisatin demethylase was indicative of the potential of Phain to detoxify its environment from the terpenoid phytoalexins produced by its host as a defense mechanism. Proteomic analysis revealed the potential survival strategies of Phain under the snow, which included the production of antifreeze proteins, trehalose synthesis enzymes, desaturases, proteins related to elongation of very long-chain fatty acids, and stress protein responses. Study of protein GH11 endoxylanase expressed in Escherichia coli showed an acidic optimum pH (pH 5.0) and a low optimum temperature (45 °C), which is reflective of the living conditions of the fungus. Mass spectrometry analysis of the methanol extract of Phain, incubated at - 3 °C and 22 °C, revealed differences in the produced metabolites. Both genomic and mass spectrometry analyses showed the ability of Phain to adapt its metabolic processes and secretome to freezing temperatures through the production of osmoprotectant and cryoprotectant metabolites. This comprehensive exploration of Phain's genome sequence, proteome, and secretome not only advances our understanding of its unique adaptive mechanisms but also expands the possibilities of biotechnological applications.

Highly alkali-stable and cellulase-free xylanases from Fusarium sp. 21 and their application in clarification of orange juice

Xylanase is a versatile tool in the food, fiber biobleaching and biofuel industries. Here, to discover new enzyme with special properties, we cloned three xylanases (Xyn11A, Xyn11B, and Xyn11C) by mining the genome of the xylanase producing fungus strain Fusarium sp. 21, biochemically characterized these enzyme and explored their potential application in juice processing. Both Xyn11A and Xyn11B had an optimal pH of 6.0 and optimal temperature of 45 °C, and retained >90% of the residual activity at pH range of 5-10.5 for 24 h. Xyn11C displayed the maximum activity at pH 5.0 and 45 °C and outstanding pH stability with a minimal loss of activity in the pH range of 2.0-10.5. These three xylanases displayed a strong specificity towards beechwood and corncob xylan, with no activity for other substrates. Xyn11A showed much a higher activity against corncob xylan, while Xyn11B and Xyn11C presented higher activities against beechwood xylan. Xyn11A catalyzed the hydrolysis of beechwood xylan with a K_m of 4.25 ± 0.29 mg·mL^-1 and k_cat/K_m of 30.34 ± 0.65 mL·s^-1·mg^-1, while the hydrolysis of corncob xylan had Km and k_cat/K_m values of 14.73 ± 1.43 mg·mL^-1and 26.48 ± 0.11 mL·s^-1·mg^-1, respectively. Xyn11B and Xyn11C hydrolyzed beechwood xylan with Km of 9.8 ± 0.69 mg·mL^-1, and 4.89 ± 0.38 mg·mL^-1and k_cat/K_m values of 45.07 ± 1.66 mL^-1·mg^-1, and 26.95 ± 0.67 mL·s^-1·mg^-1, respectively. Beechwood xylan hydrolysates catalyzed by these three xylanases contained xylobiose, xylotriose and xylooligosaccharides (XOS). The clarification of orange juice was improved when treated with these three xylanases. Conclusively, the desirable pH stability and substrate specificity make Xyn11A, Xyn11B and Xyn11C have high potential for application in fiber biobleaching, wine and fruit juice clarification, as well as probiotic XOS production.