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Computational design of Lactobacillus Acidophilus α-L-rhamnosidase to increase its structural stability
α-L-rhamnosidase catalyzes hydrolysis of the terminal α-L-rhamnose from various natural rhamnoglycosides, including naringin and hesperidin, and has various applications such as debittering of citrus juices in the food industry and flavonoid derhamnosylation in the pharmaceutical industry. However,...
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Published in: | PloS one 2022-01, Vol.17 (5), p.e0268953-e0268953 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | α-L-rhamnosidase catalyzes hydrolysis of the terminal α-L-rhamnose from various natural rhamnoglycosides, including naringin and hesperidin, and has various applications such as debittering of citrus juices in the food industry and flavonoid derhamnosylation in the pharmaceutical industry. However, its activity is lost at high temperatures, limiting its usage. To improve Lactobacillus acidophilus α-L-rhamnosidase stability, we employed molecular dynamics (MD) to identify a highly flexible region, as evaluated by its root mean square fluctuation (RMSF) value, and computational protein design (Rosetta) to increase rigidity and favorable interactions of residues in highly flexible regions. MD results show that five regions have the highest flexibilities and were selected for design by Rosetta. Twenty-one designed mutants with the best ΔΔG at each position and ΔΔG < 0 REU were simulated at high temperature. Eight designed mutants with ΔRMSF of highly flexible regions lower than -10.0% were further simulated at the optimum temperature of the wild type. N88Q, N202V, G207D, Q209M, N211T and Y213K mutants were predicted to be more stable and could maintain their native structures better than the wild type due to increased hydrogen bond interactions of designed residues and their neighboring residues. These designed mutants are promising enzymes with high potential for stability improvement. |
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ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0268953 |