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© 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

[...]genetic engineering has been used to construct more efficient enzymes for industrial applications through mutations [3]. From all possible mutations, experimental techniques can evaluate only hundreds of them. [...]a previous selection with a computational method may reduce costs and allow a higher number of tests, with promising mutated enzymes. [...]free energy calculations are not able to estimate with accuracy the impact of a mutation in an enzyme, the interaction with substrates and products, and the protein motion for more than a few examples. [...]the signature of glucose-tolerant β-glucosidases previously characterized can be used to define if mutations in non-tolerant β-glucosidases make their signature similar to a tolerant β-glucosidase or not. 2.2.1 Data Collection and Manual Classification of Mutation Effects We collected 27 mutations in β-glucosidases from the literature and the UniProt database (https://uniprot.org) (Table 1).

Details

Title
A Computational Method to Propose Mutations in Enzymes Based on Structural Signature Variation (SSV)
Author
Batista Mariano, Diego César; Lucianna Helene Santos; Karina dos Santos Machado; Werhli, Adriano Velasque; Leonardo Henrique França de Lima; Raquel Cardoso de Melo-Minardi
Publication year
2019
Publication date
2019
Publisher
MDPI AG
ISSN
16616596
e-ISSN
14220067
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2331906098
Copyright
© 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.