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dc.contributor.authorGonzález Garcinuño, Álvaro 
dc.contributor.authorTabernero de Paz, Antonio 
dc.contributor.authorMarcelo, Gema
dc.contributor.authorMartín del Valle, Eva María 
dc.date.accessioned2026-01-16T10:05:21Z
dc.date.available2026-01-16T10:05:21Z
dc.date.issued2020
dc.identifier.citationÁlvaro 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)es_ES
dc.identifier.issn0141-8130
dc.identifier.urihttp://hdl.handle.net/10366/168901
dc.description.abstract[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.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.subjectLevanes_ES
dc.subjectKinetic modelinges_ES
dc.subjectSelf-assemblyes_ES
dc.titleA comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modelinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://doi.org/10.1016/j.ijbiomac.2019.10.076es_ES
dc.identifier.doi10.1016/j.ijbiomac.2019.10.076
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleInternational Journal of Biological Macromoleculeses_ES
dc.volume.number147es_ES
dc.page.initial1089es_ES
dc.page.final1098es_ES
dc.type.hasVersioninfo:eu-repo/semantics/draftes_ES


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