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A Structural In Silico Analysis of the Immunogenicity of L-Asparaginase from IPenicillium cerradense/I

L-asparaginase is an essential drug used to treat acute lymphoid leukemia (ALL), a cancer of high prevalence in children. Several adverse reactions associated with L-asparaginase have been observed, mainly caused by immunogenicity and allergenicity. Some strategies have been adopted, such as searchi...

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Bibliographic Details
Published in:International journal of molecular sciences 2024-05, Vol.25 (9)
Main Authors: Andrade, Kellen Cruvinel Rodrigues, Homem-de-Mello, Mauricio, Motta, Julia Almeida, Borges, Marina Guimarães, de Abreu, Joel Antônio Cordeiro, de Souza, Paula Monteiro, Pessoa, Adalberto, Pappas, Georgios J, de Oliveira Magalhães, Pérola
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Language:English
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Summary:L-asparaginase is an essential drug used to treat acute lymphoid leukemia (ALL), a cancer of high prevalence in children. Several adverse reactions associated with L-asparaginase have been observed, mainly caused by immunogenicity and allergenicity. Some strategies have been adopted, such as searching for new microorganisms that produce the enzyme and applying protein engineering. Therefore, this work aimed to elucidate the molecular structure and predict the immunogenic profile of L-asparaginase from Penicillium cerradense, recently revealed as a new fungus of the genus Penicillium and producer of the enzyme, as a motivation to search for alternatives to bacterial L-asparaginase. In the evolutionary relationship, L-asparaginase from P. cerradense closely matches Aspergillus species. Using in silico tools, we characterized the enzyme as a protein fragment of 378 amino acids (39 kDa), including a signal peptide containing 17 amino acids, and the isoelectric point at 5.13. The oligomeric state was predicted to be a homotetramer. Also, this L-asparaginase presented a similar immunogenicity response (T- and B-cell epitopes) compared to Escherichia coli and Dickeya chrysanthemi enzymes. These results suggest a potentially useful L-asparaginase, with insights that can drive strategies to improve enzyme production.
ISSN:1422-0067
1422-0067
DOI:10.3390/ijms25094788