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DOE OSTI · 1578225

Enhancing subtilisin thermostability through a modified normalized B-factor analysis and loop-grafting strategy

Abstract

Rational design–guided improvement of protein thermostability typically requires identification of residues or regions contributing to instability and introduction of mutations into these residues or regions. One popular method, B-FIT, utilizes B-factors to identify unstable residues or regions and combines them with other strategies, such as directed evolution. Here, we performed structure-based engineering to improve the thermostability of the subtilisin E-S7 (SES7) peptidase. The B-value of each residue was redefined in a normalized B-factor calculation, which was implemented with a refined bioinformatics analysis strategy to identify the critical area (loop 158–162) related to flexibility and to screen for suitable thermostable motif sequences in the Protein Data Bank that can act as transplant loops. In total, we analyzed 445 structures and identified 29 thermostable motifs as candidates. Using these motifs as a starting point, we performed iterative homologous modeling to obtain a desirable chimera loop and introduced five different mutations into this loop to construct thermostable SES7 proteins. Differential scanning fluorimetry revealed increases of 7.3 °C in the melting temperature of an SES7 variant designated M5 compared with the WT. The X-ray crystallographic structure of this variant was resolved at 1.96 Å resolution. The crystal structure disclosed that M5 forms more hydrogen bonds than the WT protein, consistent with design and molecular dynamics simulation results. In summary, the modified B-FIT strategy reported here has yielded a subtilisin variant with improved thermostability and promising industrial applications, supporting the notion that this modified method is a powerful tool for protein engineering.

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Tang, Heng, Shi, Ke, Shi, Cheng, Aihara, Hideki, Zhang, Juan, Du, Guocheng. 2019-10-15. Enhancing subtilisin thermostability through a modified normalized B-factor analysis and loop-grafting strategy. https://doi.org/10.1074/jbc.ra119.010658

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