Improving the Thermostability of Xylanase A from Bacillus subtilis by Combining Bioinformatics and Electrostatic Interactions Optimization
The rational improvement of the enzyme catalytic activity is one of the most significant challenges in biotechnology. Most conventional strategies used to engineer enzymes involve selecting mutations to increase their thermostability. Determining good criteria for choosing these substitutions contin...
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Published in | The journal of physical chemistry. B Vol. 125; no. 17; pp. 4359 - 4367 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
06.05.2021
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Subjects | |
Online Access | Get full text |
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Summary: | The rational improvement of the enzyme catalytic activity is one of the most significant challenges in biotechnology. Most conventional strategies used to engineer enzymes involve selecting mutations to increase their thermostability. Determining good criteria for choosing these substitutions continues to be a challenge. In this work, we combine bioinformatics, electrostatic analysis, and molecular dynamics to predict beneficial mutations that may improve the thermostability of XynA from Bacillus subtilis. First, the Tanford–Kirkwood surface accessibility method is used to characterize each ionizable residue contribution to the protein native state stability. Residues identified to be destabilizing were mutated with the corresponding residues determined by the consensus or ancestral sequences at the same locations. Five mutants (K99T/N151D, K99T, S31R, N151D, and K154A) were investigated and compared with 12 control mutants derived from experimental approaches from the literature. Molecular dynamics results show that the mutants exhibited folding temperatures in the order K99T > K99T/N151D > S31R > N151D > WT > K154A. The combined approaches employed provide an effective strategy for low-cost enzyme optimization needed for large-scale biotechnological and medical applications. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1520-6106 1520-5207 |
DOI: | 10.1021/acs.jpcb.1c01253 |