Enhancing the Thermostability of Rhizomucor miehei Lipase with a Limited Screening Library by Rational-Design Point Mutations and Disulfide Bonds

Rhizomucor miehei lipase (RML), as a kind of eukaryotic protein catalyst, plays an important role in the food, organic chemical, and biofuel industries. However, RML retains its catalytic activity below 50 degrees C, which limits its industrial applications at higher temperatures. Soluble expression of this eukaryotic protein in Escherichia coli not only helps to screen for thermostable mutants quickly but also provides the opportunity to develop rapid and effective ways to enhance the thermal stability of eukaryotic proteins. Therefore, in this study, RML was engineered using multiple computational design methods, followed by filtration via conservation analysis and functional region assessment. We successfully obtained a limited screening library (only 36 candidates) to validate thermostable single point mutants, among which 24 of the candidates showed higher thermostability and 13 point mutations resulted in an apparent melting temperature (T-m(app)) of at least 1 degrees C higher. Furthermore, both of the two disulfide bonds predicted from four rational-design algorithms were further introduced and found to stabilize RML. The most stable mutant, with T18K/T22I/E230I/S56C-N63C/V189C-D238C mutations, exhibited a 14.3 degrees C-higher T-m(app) and a 12.5-fold increase in half-life at 70 degrees C. The catalytic efficiency of the engineered lipase was 39% higher than that of the wild type. The results demonstrate that rationally designed point mutations and disulfide bonds can effectively reduce the number of screened clones to enhance the thermostability of RML. IMPORTANCE R. miehei lipase, whose structure is well established, can be widely applied in diverse chemical processes. Soluble expression of R. miehei lipase in E. coli provides an opportunity to explore efficient methods for enhancing eukaryotic protein thermostability. This study highlights a strategy that combines computational algorithms to predict single point mutations and disulfide bonds in RML without losing catalytic activity. Through this strategy, an RML variant with greatly enhanced thermostability was obtained. This study provides a competitive alternative for wildtype RML in practical applications and further a rapid and effective strategy for thermostability engineering.