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ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria
Multi-drug resistance in bacteria is a major health problem worldwide. To overcome this issue, new approaches allowing for the identification and development of antibacterial agents are urgently needed. Peptides, due to their binding specificity and low expected side effects, are promising candidate...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9774453/ https://www.ncbi.nlm.nih.gov/pubmed/36551365 http://dx.doi.org/10.3390/antibiotics11121708 |
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author | Ruiz-Blanco, Yasser B. Agüero-Chapin, Guillermin Romero-Molina, Sandra Antunes, Agostinho Olari, Lia-Raluca Spellerberg, Barbara Münch, Jan Sanchez-Garcia, Elsa |
author_facet | Ruiz-Blanco, Yasser B. Agüero-Chapin, Guillermin Romero-Molina, Sandra Antunes, Agostinho Olari, Lia-Raluca Spellerberg, Barbara Münch, Jan Sanchez-Garcia, Elsa |
author_sort | Ruiz-Blanco, Yasser B. |
collection | PubMed |
description | Multi-drug resistance in bacteria is a major health problem worldwide. To overcome this issue, new approaches allowing for the identification and development of antibacterial agents are urgently needed. Peptides, due to their binding specificity and low expected side effects, are promising candidates for a new generation of antibiotics. For over two decades, a large diversity of antimicrobial peptides (AMPs) has been discovered and annotated in public databases. The AMP family encompasses nearly 20 biological functions, thus representing a potentially valuable resource for data mining analyses. Nonetheless, despite the availability of machine learning-based approaches focused on AMPs, these tools lack evidence of successful application for AMPs’ discovery, and many are not designed to predict a specific function for putative AMPs, such as antibacterial activity. Consequently, among the apparent variety of data mining methods to screen peptide sequences for antibacterial activity, only few tools can deal with such task consistently, although with limited precision and generally no information about the possible targets. Here, we addressed this gap by introducing a tool specifically designed to identify antibacterial peptides (ABPs) with an estimation of which type of bacteria is susceptible to the action of these peptides, according to their response to the Gram-staining assay. Our tool is freely available via a web server named ABP-Finder. This new method ranks within the top state-of-the-art ABP predictors, particularly in terms of precision. Importantly, we showed the successful application of ABP-Finder for the screening of a large peptide library from the human urine peptidome and the identification of an antibacterial peptide. |
format | Online Article Text |
id | pubmed-9774453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97744532022-12-23 ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria Ruiz-Blanco, Yasser B. Agüero-Chapin, Guillermin Romero-Molina, Sandra Antunes, Agostinho Olari, Lia-Raluca Spellerberg, Barbara Münch, Jan Sanchez-Garcia, Elsa Antibiotics (Basel) Article Multi-drug resistance in bacteria is a major health problem worldwide. To overcome this issue, new approaches allowing for the identification and development of antibacterial agents are urgently needed. Peptides, due to their binding specificity and low expected side effects, are promising candidates for a new generation of antibiotics. For over two decades, a large diversity of antimicrobial peptides (AMPs) has been discovered and annotated in public databases. The AMP family encompasses nearly 20 biological functions, thus representing a potentially valuable resource for data mining analyses. Nonetheless, despite the availability of machine learning-based approaches focused on AMPs, these tools lack evidence of successful application for AMPs’ discovery, and many are not designed to predict a specific function for putative AMPs, such as antibacterial activity. Consequently, among the apparent variety of data mining methods to screen peptide sequences for antibacterial activity, only few tools can deal with such task consistently, although with limited precision and generally no information about the possible targets. Here, we addressed this gap by introducing a tool specifically designed to identify antibacterial peptides (ABPs) with an estimation of which type of bacteria is susceptible to the action of these peptides, according to their response to the Gram-staining assay. Our tool is freely available via a web server named ABP-Finder. This new method ranks within the top state-of-the-art ABP predictors, particularly in terms of precision. Importantly, we showed the successful application of ABP-Finder for the screening of a large peptide library from the human urine peptidome and the identification of an antibacterial peptide. MDPI 2022-11-26 /pmc/articles/PMC9774453/ /pubmed/36551365 http://dx.doi.org/10.3390/antibiotics11121708 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ruiz-Blanco, Yasser B. Agüero-Chapin, Guillermin Romero-Molina, Sandra Antunes, Agostinho Olari, Lia-Raluca Spellerberg, Barbara Münch, Jan Sanchez-Garcia, Elsa ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria |
title | ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria |
title_full | ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria |
title_fullStr | ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria |
title_full_unstemmed | ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria |
title_short | ABP-Finder: A Tool to Identify Antibacterial Peptides and the Gram-Staining Type of Targeted Bacteria |
title_sort | abp-finder: a tool to identify antibacterial peptides and the gram-staining type of targeted bacteria |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9774453/ https://www.ncbi.nlm.nih.gov/pubmed/36551365 http://dx.doi.org/10.3390/antibiotics11121708 |
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