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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...

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Autores principales: Bárcenas, Oriol, Pintado-Grima, Carlos, Sidorczuk, Katarzyna, Teufel, Felix, Nielsen, Henrik, Ventura, Salvador, Burdukiewicz, Michał
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
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/.
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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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