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AllerCatPro 2.0: a web server for predicting protein allergenicity potential

Proteins in food and personal care products can pose a risk for an immediate immunoglobulin E (IgE)-mediated allergic response. Bioinformatic tools can assist to predict and investigate the allergenic potential of proteins. Here we present AllerCatPro 2.0, a web server that can be used to predict pr...

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Autores principales: Nguyen, Minh N, Krutz, Nora L, Limviphuvadh, Vachiranee, Lopata, Andreas L, Gerberick, G Frank, Maurer-Stroh, Sebastian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252832/
https://www.ncbi.nlm.nih.gov/pubmed/35640594
http://dx.doi.org/10.1093/nar/gkac446
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author Nguyen, Minh N
Krutz, Nora L
Limviphuvadh, Vachiranee
Lopata, Andreas L
Gerberick, G Frank
Maurer-Stroh, Sebastian
author_facet Nguyen, Minh N
Krutz, Nora L
Limviphuvadh, Vachiranee
Lopata, Andreas L
Gerberick, G Frank
Maurer-Stroh, Sebastian
author_sort Nguyen, Minh N
collection PubMed
description Proteins in food and personal care products can pose a risk for an immediate immunoglobulin E (IgE)-mediated allergic response. Bioinformatic tools can assist to predict and investigate the allergenic potential of proteins. Here we present AllerCatPro 2.0, a web server that can be used to predict protein allergenicity potential with better accuracy than other computational methods and new features that help assessors making informed decisions. AllerCatPro 2.0 predicts the similarity between input proteins using both their amino acid sequences and predicted 3D structures towards the most comprehensive datasets of reliable proteins associated with allergenicity. These datasets currently include 4979 protein allergens, 162 low allergenic proteins, and 165 autoimmune allergens with manual expert curation from the databases of WHO/International Union of Immunological Societies (IUIS), Comprehensive Protein Allergen Resource (COMPARE), Food Allergy Research and Resource Program (FARRP), UniProtKB and Allergome. Various examples of profilins, autoimmune allergens, low allergenic proteins, very large proteins, and nucleotide input sequences showcase the utility of AllerCatPro 2.0 for predicting protein allergenicity potential. The AllerCatPro 2.0 web server is freely accessible at https://allercatpro.bii.a-star.edu.sg.
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spelling pubmed-92528322022-07-05 AllerCatPro 2.0: a web server for predicting protein allergenicity potential Nguyen, Minh N Krutz, Nora L Limviphuvadh, Vachiranee Lopata, Andreas L Gerberick, G Frank Maurer-Stroh, Sebastian Nucleic Acids Res Web Server Issue Proteins in food and personal care products can pose a risk for an immediate immunoglobulin E (IgE)-mediated allergic response. Bioinformatic tools can assist to predict and investigate the allergenic potential of proteins. Here we present AllerCatPro 2.0, a web server that can be used to predict protein allergenicity potential with better accuracy than other computational methods and new features that help assessors making informed decisions. AllerCatPro 2.0 predicts the similarity between input proteins using both their amino acid sequences and predicted 3D structures towards the most comprehensive datasets of reliable proteins associated with allergenicity. These datasets currently include 4979 protein allergens, 162 low allergenic proteins, and 165 autoimmune allergens with manual expert curation from the databases of WHO/International Union of Immunological Societies (IUIS), Comprehensive Protein Allergen Resource (COMPARE), Food Allergy Research and Resource Program (FARRP), UniProtKB and Allergome. Various examples of profilins, autoimmune allergens, low allergenic proteins, very large proteins, and nucleotide input sequences showcase the utility of AllerCatPro 2.0 for predicting protein allergenicity potential. The AllerCatPro 2.0 web server is freely accessible at https://allercatpro.bii.a-star.edu.sg. Oxford University Press 2022-05-30 /pmc/articles/PMC9252832/ /pubmed/35640594 http://dx.doi.org/10.1093/nar/gkac446 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://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
Nguyen, Minh N
Krutz, Nora L
Limviphuvadh, Vachiranee
Lopata, Andreas L
Gerberick, G Frank
Maurer-Stroh, Sebastian
AllerCatPro 2.0: a web server for predicting protein allergenicity potential
title AllerCatPro 2.0: a web server for predicting protein allergenicity potential
title_full AllerCatPro 2.0: a web server for predicting protein allergenicity potential
title_fullStr AllerCatPro 2.0: a web server for predicting protein allergenicity potential
title_full_unstemmed AllerCatPro 2.0: a web server for predicting protein allergenicity potential
title_short AllerCatPro 2.0: a web server for predicting protein allergenicity potential
title_sort allercatpro 2.0: a web server for predicting protein allergenicity potential
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252832/
https://www.ncbi.nlm.nih.gov/pubmed/35640594
http://dx.doi.org/10.1093/nar/gkac446
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