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2019 | 137 | 31-41
Article title

The expression level of a recombinant lipase predicted in silico by different codon optimization algorithms

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Abstracts
EN
Optimizing codons of gene of interest has offered a value-added way to increase heterologous expression of proteins. Different algorithms have been designed to achieve this purpose. These algorithms make use of parameters such as codon Adaptation index (CAI), codon context (CC), percentage guanine-cytosine (GC) content and RNA instability for predicting optimal codons responsible for increased protein expression. Lipase 3646 is an enzyme with great potential for industrial applications. This enzymes has been described to possess thermostable properties with relative stability in high alkaline pH and at different concentrations of organic solvents and inhibitors. This research therefore used JCat, Codon optimization online (COOL), presyndocon and ExpOptimizer algorithms to predict expression level of lipase 3646 enzyme in silico by optimizing its gene coding sequence. The results showed that there were variations in the CAI generated by the algorithms for the same 3646 DNA sequence which suggests that each algorithm is specific for its own generated CAI. COOL algorithm prediction based on other parameters showed good results for potential expression of the lipase. Thus, we recommend COOL algorithm for codon optimization of the lipase 3646 gene for industrial applications.
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Year
Volume
137
Pages
31-41
Physical description
Contributors
  • Department of Cell Biology and Genetics, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria
  • Department of Biochemistry, College of Medicine, University of Lagos, Idi-Araba, Lagos, Nigeria
  • Molecular Biology and Bioinformatics Unit, Biologix Support Services Limited, Anthony, Lagos, Nigeria
author
  • Department of Cell Biology and Genetics, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria
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Document Type
article
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.psjd-4d7e51b8-2d5c-42a2-b11e-93f2f17ff38c
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