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A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale

A probabilistic discrete model for 2D protein crystal growth is presented. This model takes into account the available space and can describe growing processes of a different nature due to the versatility of its parameters, which gives the model great flexibility. The accuracy of the simulation is t...

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Detalles Bibliográficos
Autores principales: Bolos, Vicente J., Benitez, Rafael, Eleta-Lopez, Aitziber, Toca-Herrera, Jose L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384748/
https://www.ncbi.nlm.nih.gov/pubmed/30720751
http://dx.doi.org/10.3390/ma12030479
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author Bolos, Vicente J.
Benitez, Rafael
Eleta-Lopez, Aitziber
Toca-Herrera, Jose L.
author_facet Bolos, Vicente J.
Benitez, Rafael
Eleta-Lopez, Aitziber
Toca-Herrera, Jose L.
author_sort Bolos, Vicente J.
collection PubMed
description A probabilistic discrete model for 2D protein crystal growth is presented. This model takes into account the available space and can describe growing processes of a different nature due to the versatility of its parameters, which gives the model great flexibility. The accuracy of the simulation is tested against a real recrystallization experiment, carried out with the bacterial protein SbpA from Lysinibacillus sphaericus CCM2177, showing high agreement between the proposed model and the actual images of the crystal growth. Finally, it is also discussed how the regularity of the interface (i.e., the curve that separates the crystal from the substrate) affects the evolution of the simulation.
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spelling pubmed-63847482019-02-23 A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale Bolos, Vicente J. Benitez, Rafael Eleta-Lopez, Aitziber Toca-Herrera, Jose L. Materials (Basel) Article A probabilistic discrete model for 2D protein crystal growth is presented. This model takes into account the available space and can describe growing processes of a different nature due to the versatility of its parameters, which gives the model great flexibility. The accuracy of the simulation is tested against a real recrystallization experiment, carried out with the bacterial protein SbpA from Lysinibacillus sphaericus CCM2177, showing high agreement between the proposed model and the actual images of the crystal growth. Finally, it is also discussed how the regularity of the interface (i.e., the curve that separates the crystal from the substrate) affects the evolution of the simulation. MDPI 2019-02-04 /pmc/articles/PMC6384748/ /pubmed/30720751 http://dx.doi.org/10.3390/ma12030479 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bolos, Vicente J.
Benitez, Rafael
Eleta-Lopez, Aitziber
Toca-Herrera, Jose L.
A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale
title A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale
title_full A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale
title_fullStr A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale
title_full_unstemmed A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale
title_short A Probabilistic Model for Crystal Growth Applied to Protein Deposition at the Microscale
title_sort probabilistic model for crystal growth applied to protein deposition at the microscale
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384748/
https://www.ncbi.nlm.nih.gov/pubmed/30720751
http://dx.doi.org/10.3390/ma12030479
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