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IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants
The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the dissociation constant (pK(a)) of charged groups of seven amino acids and NH(+) and COO(−) groups at polypeptid...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Oxford University Press
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262712/ https://www.ncbi.nlm.nih.gov/pubmed/33905510 http://dx.doi.org/10.1093/nar/gkab295 |
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author | Kozlowski, Lukasz Pawel |
author_facet | Kozlowski, Lukasz Pawel |
author_sort | Kozlowski, Lukasz Pawel |
collection | PubMed |
description | The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the dissociation constant (pK(a)) of charged groups of seven amino acids and NH(+) and COO(−) groups at polypeptide termini. Information regarding isoelectric point and pK(a) is extensively used in two-dimensional gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), crystallisation, and mass spectrometry. Therefore, there is a strong need for the in silico prediction of isoelectric point and pK(a) values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pK(a) values using a mixture of deep learning and support vector regression models. The prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pK(a) using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster. The IPC 2.0 webserver is freely available at www.ipc2-isoelectric-point.org |
format | Online Article Text |
id | pubmed-8262712 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82627122021-07-08 IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants Kozlowski, Lukasz Pawel Nucleic Acids Res Web Server Issue The isoelectric point is the pH at which a particular molecule is electrically neutral due to the equilibrium of positive and negative charges. In proteins and peptides, this depends on the dissociation constant (pK(a)) of charged groups of seven amino acids and NH(+) and COO(−) groups at polypeptide termini. Information regarding isoelectric point and pK(a) is extensively used in two-dimensional gel electrophoresis (2D-PAGE), capillary isoelectric focusing (cIEF), crystallisation, and mass spectrometry. Therefore, there is a strong need for the in silico prediction of isoelectric point and pK(a) values. In this paper, I present Isoelectric Point Calculator 2.0 (IPC 2.0), a web server for the prediction of isoelectric points and pK(a) values using a mixture of deep learning and support vector regression models. The prediction accuracy (RMSD) of IPC 2.0 for proteins and peptides outperforms previous algorithms: 0.848 versus 0.868 and 0.222 versus 0.405, respectively. Moreover, the IPC 2.0 prediction of pK(a) using sequence information alone was better than the prediction from structure-based methods (0.576 versus 0.826) and a few folds faster. The IPC 2.0 webserver is freely available at www.ipc2-isoelectric-point.org Oxford University Press 2021-04-27 /pmc/articles/PMC8262712/ /pubmed/33905510 http://dx.doi.org/10.1093/nar/gkab295 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Web Server Issue Kozlowski, Lukasz Pawel IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants |
title | IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants |
title_full | IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants |
title_fullStr | IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants |
title_full_unstemmed | IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants |
title_short | IPC 2.0: prediction of isoelectric point and pK(a) dissociation constants |
title_sort | ipc 2.0: prediction of isoelectric point and pk(a) dissociation constants |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262712/ https://www.ncbi.nlm.nih.gov/pubmed/33905510 http://dx.doi.org/10.1093/nar/gkab295 |
work_keys_str_mv | AT kozlowskilukaszpawel ipc20predictionofisoelectricpointandpkadissociationconstants |