<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Kappa-carrageenase (EC 3.2.1.83) is a glycoside hydrolase family 16 (GH16) member that could specifically hydrolyse kappa-carrageenans to kappa-carrageenan oligosaccharides. Kappa-carrageenase enzymes have attracted much interest due to their numerous potential applications in biomedical and physiological fields, bioethanol production, and textile industry. In the present study, physicochemical, secondary structure, structural properties including homology modeling, refinement, and model quality validation, and functional analyses of the kappacarrageenanse from <italic>Pseudomonas fluorescens</italic> using various bioinformatic tools were conducted. The protein was found to be stable and acidic in nature. Secondary structure prediction revealed that the presence of random coil is more dominated in the protein sequence followed by extended strand, α-helix, and β-turn. Protein-protein interaction prediction revealed ten potential functional partners. This bioinformatic characterization provides for the first time insights into fundamental characteristics of the predicted Kappa-carrageenase of <italic>P. fluorescens</italic>, which may be useful for elucidating its applications and for further expression and characterization studies.</p>
</abstract>

Kappa-carrageenase (EC 3.2.1.83) is a glycoside hydrolase family 16 (GH16) member that could specifically hydrolyse kappa-carrageenans to kappa-carrageenan oligosaccharides. Kappa-carrageenase enzymes have attracted much interest due to their numerous potential applications in biomedical and physiological fields, bioethanol production, and textile industry. In the present study, physicochemical, secondary structure, structural properties including homology modeling, refinement, and model quality validation, and functional analyses of the kappacarrageenanse from Pseudomonas fluorescens using various bioinformatic tools were conducted. The protein was found to be stable and acidic in nature. Secondary structure prediction revealed that the presence of random coil is more dominated in the protein sequence followed by extended strand, α-helix, and β-turn. Protein-protein interaction prediction revealed ten potential functional partners. This bioinformatic characterization provides for the first time insights into fundamental characteristics of the predicted Kappa-carrageenase of P. fluorescens, which may be useful for elucidating its applications and for further expression and characterization studies.

Bioinformatic Characterization of a Kappa-Carrageenase from <italic>Pseudomonas fluorescens</italic>

Département de Biologie, Faculté des Sciences et Technologie

Physiologie, Physiopathologie et Biochimie de la Nutrition

Département de Biologie, Faculté des Sciences de la Nature et de la Vie et Sciences de la Terre

Laboratoire de Biologie des Systèmes Microbiens (LBSM)

Banat’s University of Life Sciences “King Michael I of Romania”

Advanced Research in Life Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Bioinformatic Characterization of a Kappa-Carrageenase from 

Kappa-carrageenase (EC 3.2.1.83) is a glycoside hydrolase family 16 (GH16) member that could specifically hydrolyse kappa-carrageenans to kappa-carrageenan...

Bioinformatic Characterization of a Kappa-Carrageenase from Pseudomonas fluorescens

Pubblicato online: 22 ott 2022

Pagine: 33 - 39

Ricevuto: 01 set 2022

Accettato: 01 ott 2022

DOI: https://doi.org/10.2478/arls-2022-0036

Parole chiave
Kappa-carrageenase, bioinformatic tools, homology modeling, bioinformatic characterization

© 2022 Mahfoud Bakli et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Bioinformatic Characterization of a Kappa-Carrageenase from Pseudomonas fluorescens

Pubblicato online: 22 ott 2022

Pagine: 33 - 39

Ricevuto: 01 set 2022

Accettato: 01 ott 2022

DOI: https://doi.org/10.2478/arls-2022-0036

Parole chiaveKappa-carrageenase, bioinformatic tools, homology modeling, bioinformatic characterization

© 2022 Mahfoud Bakli et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Kappa-carrageenase, bioinformatic tools, homology modeling, bioinformatic characterization