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The dynamic landscape of peptide activity prediction
Peptides are known to possess a plethora of beneficial properties and activities: antimicrobial, anticancer, anti-inflammatory or the ability to cross the blood–brain barrier are only a few examples of their functional diversity. For this reason, bioinformaticians are constantly developing and upgra...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712827/ https://www.ncbi.nlm.nih.gov/pubmed/36467580 http://dx.doi.org/10.1016/j.csbj.2022.11.043 |
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author | Bárcenas, Oriol Pintado-Grima, Carlos Sidorczuk, Katarzyna Teufel, Felix Nielsen, Henrik Ventura, Salvador Burdukiewicz, Michał |
author_facet | Bárcenas, Oriol Pintado-Grima, Carlos Sidorczuk, Katarzyna Teufel, Felix Nielsen, Henrik Ventura, Salvador Burdukiewicz, Michał |
author_sort | Bárcenas, Oriol |
collection | PubMed |
description | Peptides are known to possess a plethora of beneficial properties and activities: antimicrobial, anticancer, anti-inflammatory or the ability to cross the blood–brain barrier are only a few examples of their functional diversity. For this reason, bioinformaticians are constantly developing and upgrading models to predict their activity in silico, generating a steadily increasing number of available tools. Although these efforts have provided fruitful outcomes in the field, the vast and diverse amount of resources for peptide prediction can turn a simple prediction into an overwhelming searching process to find the optimal tool. This minireview aims at providing a systematic and accessible analysis of the complex ecosystem of peptide activity prediction, showcasing the variability of existing models for peptide assessment, their domain specialization and popularity. Moreover, we also assess the reproducibility of such bioinformatics tools and describe tendencies observed in their development. The list of tools is available under https://biogenies.info/peptide-prediction-list/. |
format | Online Article Text |
id | pubmed-9712827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-97128272022-12-02 The dynamic landscape of peptide activity prediction Bárcenas, Oriol Pintado-Grima, Carlos Sidorczuk, Katarzyna Teufel, Felix Nielsen, Henrik Ventura, Salvador Burdukiewicz, Michał Comput Struct Biotechnol J Mini Review Peptides are known to possess a plethora of beneficial properties and activities: antimicrobial, anticancer, anti-inflammatory or the ability to cross the blood–brain barrier are only a few examples of their functional diversity. For this reason, bioinformaticians are constantly developing and upgrading models to predict their activity in silico, generating a steadily increasing number of available tools. Although these efforts have provided fruitful outcomes in the field, the vast and diverse amount of resources for peptide prediction can turn a simple prediction into an overwhelming searching process to find the optimal tool. This minireview aims at providing a systematic and accessible analysis of the complex ecosystem of peptide activity prediction, showcasing the variability of existing models for peptide assessment, their domain specialization and popularity. Moreover, we also assess the reproducibility of such bioinformatics tools and describe tendencies observed in their development. The list of tools is available under https://biogenies.info/peptide-prediction-list/. Research Network of Computational and Structural Biotechnology 2022-11-24 /pmc/articles/PMC9712827/ /pubmed/36467580 http://dx.doi.org/10.1016/j.csbj.2022.11.043 Text en © 2022 Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Mini Review Bárcenas, Oriol Pintado-Grima, Carlos Sidorczuk, Katarzyna Teufel, Felix Nielsen, Henrik Ventura, Salvador Burdukiewicz, Michał The dynamic landscape of peptide activity prediction |
title | The dynamic landscape of peptide activity prediction |
title_full | The dynamic landscape of peptide activity prediction |
title_fullStr | The dynamic landscape of peptide activity prediction |
title_full_unstemmed | The dynamic landscape of peptide activity prediction |
title_short | The dynamic landscape of peptide activity prediction |
title_sort | dynamic landscape of peptide activity prediction |
topic | Mini Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712827/ https://www.ncbi.nlm.nih.gov/pubmed/36467580 http://dx.doi.org/10.1016/j.csbj.2022.11.043 |
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