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Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility

Protein aggregation is a hallmark of a growing number of human disorders and constitutes a major bottleneck in the manufacturing of therapeutic proteins. Therefore, there is a strong need of in-silico methods that can anticipate the aggregative properties of protein variants linked to disease and as...

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Autores principales: Kuriata, Aleksander, Iglesias, Valentin, Pujols, Jordi, Kurcinski, Mateusz, Kmiecik, Sebastian, Ventura, Salvador
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602499/
https://www.ncbi.nlm.nih.gov/pubmed/31049593
http://dx.doi.org/10.1093/nar/gkz321
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author Kuriata, Aleksander
Iglesias, Valentin
Pujols, Jordi
Kurcinski, Mateusz
Kmiecik, Sebastian
Ventura, Salvador
author_facet Kuriata, Aleksander
Iglesias, Valentin
Pujols, Jordi
Kurcinski, Mateusz
Kmiecik, Sebastian
Ventura, Salvador
author_sort Kuriata, Aleksander
collection PubMed
description Protein aggregation is a hallmark of a growing number of human disorders and constitutes a major bottleneck in the manufacturing of therapeutic proteins. Therefore, there is a strong need of in-silico methods that can anticipate the aggregative properties of protein variants linked to disease and assist the engineering of soluble protein-based drugs. A few years ago, we developed a method for structure-based prediction of aggregation properties that takes into account the dynamic fluctuations of proteins. The method has been made available as the Aggrescan3D (A3D) web server and applied in numerous studies of protein structure-aggregation relationship. Here, we present a major update of the A3D web server to version 2.0. The new features include: extension of dynamic calculations to significantly larger and multimeric proteins, simultaneous prediction of changes in protein solubility and stability upon mutation, rapid screening for functional protein variants with improved solubility, a REST-ful service to incorporate A3D calculations in automatic pipelines, and a new, enhanced web server interface. A3D 2.0 is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/
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spelling pubmed-66024992019-07-05 Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility Kuriata, Aleksander Iglesias, Valentin Pujols, Jordi Kurcinski, Mateusz Kmiecik, Sebastian Ventura, Salvador Nucleic Acids Res Web Server Issue Protein aggregation is a hallmark of a growing number of human disorders and constitutes a major bottleneck in the manufacturing of therapeutic proteins. Therefore, there is a strong need of in-silico methods that can anticipate the aggregative properties of protein variants linked to disease and assist the engineering of soluble protein-based drugs. A few years ago, we developed a method for structure-based prediction of aggregation properties that takes into account the dynamic fluctuations of proteins. The method has been made available as the Aggrescan3D (A3D) web server and applied in numerous studies of protein structure-aggregation relationship. Here, we present a major update of the A3D web server to version 2.0. The new features include: extension of dynamic calculations to significantly larger and multimeric proteins, simultaneous prediction of changes in protein solubility and stability upon mutation, rapid screening for functional protein variants with improved solubility, a REST-ful service to incorporate A3D calculations in automatic pipelines, and a new, enhanced web server interface. A3D 2.0 is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/ Oxford University Press 2019-07-02 2019-05-03 /pmc/articles/PMC6602499/ /pubmed/31049593 http://dx.doi.org/10.1093/nar/gkz321 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Web Server Issue
Kuriata, Aleksander
Iglesias, Valentin
Pujols, Jordi
Kurcinski, Mateusz
Kmiecik, Sebastian
Ventura, Salvador
Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility
title Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility
title_full Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility
title_fullStr Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility
title_full_unstemmed Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility
title_short Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility
title_sort aggrescan3d (a3d) 2.0: prediction and engineering of protein solubility
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602499/
https://www.ncbi.nlm.nih.gov/pubmed/31049593
http://dx.doi.org/10.1093/nar/gkz321
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