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    Título
    A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
    Autor(es)
    González Garcinuño, ÁlvaroUSAL authority ORCID
    Tabernero de Paz, AntonioUSAL authority ORCID
    Marcelo, Gema
    Martín del Valle, Eva MaríaUSAL authority
    Palabras clave
    Levan
    Kinetic modeling
    Self-assembly
    Fecha de publicación
    2020
    Editor
    Elsevier
    Citación
    Álvaro González-Garcinuño, Antonio Tabernero, Gema Marcelo, Eva Martín del Valle, A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling, International Journal of Biological Macromolecules, Volume 147, 2020, Pages 1089-1098, ISSN 0141-8130, https://doi.org/10.1016/j.ijbiomac.2019.10.076. (https://www.sciencedirect.com/science/article/pii/S0141813019359914)
    Resumen
    [EN]Levan nanoparticles formation is a complicated phenomenon involving simultaneously polymeric reaction kinetics and nanoparticles self-assembly theory. These phenomena are studied in this work with experimental and computationalmethodologies. Specifically, the effect of different parameters on levan kinetics and nanoparticles production in a cell-free system environment have been studied. Results point out that 37 °C is the best temperature for synthesizing levan as well as the existence of a substrate inhibition effect for polymeric reaction. This work also highlights that raffinose can be used for producing and that an increase on the ratio enzymesubstrate increases the velocity of conversion. However, the previous experimental conditions did not produce an important effect on self-assembly formed levan nanoparticles (always 110 nm) as long as the required levan concentration (CAC) for nanoparticles reorganization is achieved. To have a better understanding of these results, a model was developed to explain numerically levan kinetics and nanoparticle self-assembly. This model was built by taking into account enzyme poisoning effect (also demonstrated experimentally) and a diffusion limited cluster model for the aggregation phenomenon. Simulation results fit properly experimental data and catalytic parameters as well as predicting accurately the value of CAC for producing its reorganization into nanoparticles by self-assembly.
    URI
    https://hdl.handle.net/10366/168901
    ISSN
    0141-8130
    DOI
    10.1016/j.ijbiomac.2019.10.076
    Versión del editor
    https://doi.org/10.1016/j.ijbiomac.2019.10.076
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