Replacement P212H altered the pH-temperature profile of phytase from Aspergillus niger NII 08121

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.

Shifting the pH profiles of Staphylococcus epidermidis lipase (SEL) and Staphylococcus hyicus lipase (SHL) through generating chimeric lipases by DNA shuffling strategy

Enzymes are often required to function in a particular reaction condition by the industrial procedure. In order to identify critical residues affecting the optimum pH of Staphylococcal lipases, chimeric lipases from homologous lipases were generated via a DNA shuffling strategy. Chimeric 1 included mutations of G166S, K212E, T243A, H271Y. Chimeric 2 consisted of substitutions of K212E, T243A, H271Y. Chimeric 3 contained substitutions of K212E, R359L. From the screening results, the pH profiles for chimeric 1 and 2 lipases were shifted from pH 7 to 6. While the pH of chimeric 3 was shifted to 8. It seems the mutation of K212E in chimeric 1 and 2 decreased the pH to 6 by changing the electrostatic potential surface. Furthermore, chimeric 3 showed 10 ˚C improvement in the optimum temperature due to the rigidification of the catalytic loop through the hydrophobic interaction network. Moreover, the substrate specificity of chimeric 1 and 2 was increased towards the longer carbon length chains due to the mutation of T243A adjacent to the lid region through increasing the flexibility of the lid. Current study illustrated that directed evolution successfully modified lipase properties including optimum pH, temperature and substrate specificity through mutations, especially near catalytic and lid regions.

Engineering the residual side chains of HAP phytases to improve their pepsin resistance and catalytic efficiency

Strong resistance to proteolytic attack is important for feed enzymes. Here, we selected three predicted pepsin cleavage sites, L99, L162, and E230 (numbering from the initiator M of premature proteins), in pepsin-sensitive HAP phytases YkAPPA from Yersinia kristensenii and YeAPPA from Y. enterocolitica, which corresponded to L99, V162, and D230 in pepsin-resistant YrAPPA from Y. rohdei. We constructed mutants with different side chain structures at these sites using site-directed mutagenesis and produced all enzymes in Escherichia coli for catalytic and biochemical characterization. The substitutions E230G/A/P/R/S/T/D, L162G/A/V, L99A, L99A/L162G, and L99A/L162G/E230G improved the pepsin resistance. Moreover, E230G/A and L162G/V conferred enhanced pepsin resistance on YkAPPA and YeAPPA, increased their catalytic efficiency 1.3–2.4-fold, improved their stability at 60 °C and pH 1.0–2.0 and alleviated inhibition by metal ions. In addition, E230G increased the ability of YkAPPA and YeAPPA to hydrolyze phytate from corn meal at a high pepsin concentration and low pH, which indicated that optimization of the pepsin cleavage site side chains may enhance the pepsin resistance, improve the stability at acidic pH, and increase the catalytic activity. This study proposes an efficient approach to improve enzyme performance in monogastric animals fed feed with a high phytate content.

Novel Glucose-1-Phosphatase with High Phytase Activity and Unusual Metal Ion Activation from Soil Bacterium Pantoea sp. Strain 3.5.1

Phosphorus is an important macronutrient, but its availability in soil is limited. Many soil microorganisms improve the bioavailability of phosphate by releasing it from various organic compounds, including phytate. To investigate the diversity of phytate-hydrolyzing bacteria in soil, we sampled soils of various ecological habitats, including forest, private homesteads, large agricultural complexes, and urban landscapes. Bacterial isolate Pantoea sp. strain 3.5.1 with the highest level of phytase activity was isolated from forest soil and investigated further. The Pantoea sp. 3.5.1 agpP gene encoding a novel glucose-1-phosphatase with high phytase activity was identified, and the corresponding protein was purified to apparent homogeneity, sequenced by mass spectroscopy, and biochemically characterized. The AgpP enzyme exhibits maximum activity and stability at pH 4.5 and at 37°C. The enzyme belongs to a group of histidine acid phosphatases and has the lowest Km values toward phytate, glucose-6-phosphate, and glucose-1-phosphate. Unexpectedly, stimulation of enzymatic activity by several divalent metal ions was observed for the AgpP enzyme. High-performance liquid chromatography (HPLC) and high-performance ion chromatography (HPIC) analyses of phytate hydrolysis products identify dl-myo-inositol 1,2,4,5,6-pentakisphosphate as the final product of the reaction, indicating that the Pantoea sp. AgpP glucose-1-phosphatase can be classified as a 3-phytase. The identification of the Pantoea sp. AgpP phytase and its unusual regulation by metal ions highlight the remarkable diversity of phosphorus metabolism regulation in soil bacteria. Furthermore, our data indicate that natural forest soils harbor rich reservoirs of novel phytate-hydrolyzing enzymes with unique biochemical features.