Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures
The thermostable α-amylase derived from Bacillus licheniformis (BLA) has multiple advantages, including enhancing the mass transfer rate and by reducing microbial contamination in starch hydrolysis. Nonetheless, the application of BLA is constrained by the accessibility and stability of enzymes capa...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037024000308 |
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| author | Shuai Fan Xudong Lü Xiyu Wei Ruijie Lü Cuiyue Feng Yuanyuan Jin Maocai Yan Zhaoyong Yang |
| author_facet | Shuai Fan Xudong Lü Xiyu Wei Ruijie Lü Cuiyue Feng Yuanyuan Jin Maocai Yan Zhaoyong Yang |
| author_sort | Shuai Fan |
| collection | DOAJ |
| description | The thermostable α-amylase derived from Bacillus licheniformis (BLA) has multiple advantages, including enhancing the mass transfer rate and by reducing microbial contamination in starch hydrolysis. Nonetheless, the application of BLA is constrained by the accessibility and stability of enzymes capable of achieving high conversion rates at elevated temperatures. Moreover, the thermotolerance of BLA requires further enhancement. Here, we developed a computational strategy for constructing small and smart mutant libraries to identify variants with enhanced thermostability. Initially, molecular dynamics (MD) simulations were employed to identify the regions with high flexibility. Subsequently, FoldX, a computational design predictor, was used to design mutants by rigidifying highly flexible residues, whereas the simultaneous decrease in folding free energy assisted in improving thermostability. Through the utilization of MD and FoldX, residues K251, T277, N278, K319, and E336, situated at a distance of 5 Å from the catalytic triad, were chosen for mutation. Seventeen mutants were identified and characterized by evaluating enzymatic characteristics and kinetic parameters. The catalytic efficiency of the E271L/N278K mutant reached 184.1 g L−1 s−1, which is 1.88-fold larger than the corresponding value determined for the WT. Furthermore, the most thermostable mutant, E336S, exhibited a 1.43-fold improvement in half-life at 95 ℃, compared with that of the WT. This study, by combining computational simulation with experimental verification, establishes that potential sites can be computationally predicted to increase the activity and stability of BLA and thus provide a possible strategy by which to guide protein design. |
| first_indexed | 2024-03-07T23:52:04Z |
| format | Article |
| id | doaj.art-7fe0422e3d7049299776bbdb0b5be890 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-03-07T23:52:04Z |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-7fe0422e3d7049299776bbdb0b5be8902024-02-19T04:13:23ZengElsevierComputational and Structural Biotechnology Journal2001-03702024-12-0123982989Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperaturesShuai Fan0Xudong Lü1Xiyu Wei2Ruijie Lü3Cuiyue Feng4Yuanyuan Jin5Maocai Yan6Zhaoyong Yang7Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, ChinaInstitute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, ChinaInstitute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, ChinaSchool of Pharmacy, North China University of Science and Technology, Tangshan 063210, Hebei, ChinaSchool of Pharmacy, North China University of Science and Technology, Tangshan 063210, Hebei, ChinaInstitute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, ChinaSchool of Pharmacy, Jining Medical University, Rizhao 276800, Shandong, China; Corresponding authors.Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China; Corresponding authors.The thermostable α-amylase derived from Bacillus licheniformis (BLA) has multiple advantages, including enhancing the mass transfer rate and by reducing microbial contamination in starch hydrolysis. Nonetheless, the application of BLA is constrained by the accessibility and stability of enzymes capable of achieving high conversion rates at elevated temperatures. Moreover, the thermotolerance of BLA requires further enhancement. Here, we developed a computational strategy for constructing small and smart mutant libraries to identify variants with enhanced thermostability. Initially, molecular dynamics (MD) simulations were employed to identify the regions with high flexibility. Subsequently, FoldX, a computational design predictor, was used to design mutants by rigidifying highly flexible residues, whereas the simultaneous decrease in folding free energy assisted in improving thermostability. Through the utilization of MD and FoldX, residues K251, T277, N278, K319, and E336, situated at a distance of 5 Å from the catalytic triad, were chosen for mutation. Seventeen mutants were identified and characterized by evaluating enzymatic characteristics and kinetic parameters. The catalytic efficiency of the E271L/N278K mutant reached 184.1 g L−1 s−1, which is 1.88-fold larger than the corresponding value determined for the WT. Furthermore, the most thermostable mutant, E336S, exhibited a 1.43-fold improvement in half-life at 95 ℃, compared with that of the WT. This study, by combining computational simulation with experimental verification, establishes that potential sites can be computationally predicted to increase the activity and stability of BLA and thus provide a possible strategy by which to guide protein design.http://www.sciencedirect.com/science/article/pii/S2001037024000308Protein engineeringMolecular dynamicsα-amylaseThermostability |
| spellingShingle | Shuai Fan Xudong Lü Xiyu Wei Ruijie Lü Cuiyue Feng Yuanyuan Jin Maocai Yan Zhaoyong Yang Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures Computational and Structural Biotechnology Journal Protein engineering Molecular dynamics α-amylase Thermostability |
| title | Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures |
| title_full | Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures |
| title_fullStr | Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures |
| title_full_unstemmed | Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures |
| title_short | Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures |
| title_sort | computational design of α amylase from bacillus licheniformis to increase its activity and stability at high temperatures |
| topic | Protein engineering Molecular dynamics α-amylase Thermostability |
| url | http://www.sciencedirect.com/science/article/pii/S2001037024000308 |
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