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Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening
The day is rapidly approaching where current antibiotic therapies will no longer be effective due to the development of multi-drug resistant bacteria. Antimicrobial peptides (AMPs) are a promising class of therapeutic agents which have the potential to help address this burgeoning problem. Proline-r...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043238/ https://www.ncbi.nlm.nih.gov/pubmed/35494637 http://dx.doi.org/10.3389/fchem.2022.875233 |
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author | Handley, Thomas N. G. Li, Wenyi Welch, Nicholas G. O’Brien-Simpson, Neil M. Hossain, Mohammed Akhter Wade, John D. |
author_facet | Handley, Thomas N. G. Li, Wenyi Welch, Nicholas G. O’Brien-Simpson, Neil M. Hossain, Mohammed Akhter Wade, John D. |
author_sort | Handley, Thomas N. G. |
collection | PubMed |
description | The day is rapidly approaching where current antibiotic therapies will no longer be effective due to the development of multi-drug resistant bacteria. Antimicrobial peptides (AMPs) are a promising class of therapeutic agents which have the potential to help address this burgeoning problem. Proline-rich AMPs (PrAMPs) are a sub-class of AMPs, that have multiple modes of action including modulation of the bacterial protein folding chaperone, DnaK. They are highly effective against Gram-negative bacteria and have low toxicity to mammalian cells. Previously we used an in silico approach to identify new potential PrAMPs from the DRAMP database. Four of these peptides, antibacterial napin, attacin-C, P9, and PP30, were each chemically assembled and characterized. Together with synthetic oncocin as a reference, each peptide was then assessed for antibacterial activity against Gram-negative/Gram-positive bacteria and for in vitro DnaK modulation activity. We observed that these peptides directly modulate DnaK activity independently of eliciting or otherwise an antibiotic effect. Based on our findings, we propose a change to our previously established PrAMP definition to remove the requirement for antimicrobial activity in isolation, leaving the following classifiers: >25% proline, modulation of DnaK AND/OR the 70S ribosome, net charge of +1 or more, produced in response to bacterial infection AND/OR with pronounced antimicrobial activity. |
format | Online Article Text |
id | pubmed-9043238 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90432382022-04-28 Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening Handley, Thomas N. G. Li, Wenyi Welch, Nicholas G. O’Brien-Simpson, Neil M. Hossain, Mohammed Akhter Wade, John D. Front Chem Chemistry The day is rapidly approaching where current antibiotic therapies will no longer be effective due to the development of multi-drug resistant bacteria. Antimicrobial peptides (AMPs) are a promising class of therapeutic agents which have the potential to help address this burgeoning problem. Proline-rich AMPs (PrAMPs) are a sub-class of AMPs, that have multiple modes of action including modulation of the bacterial protein folding chaperone, DnaK. They are highly effective against Gram-negative bacteria and have low toxicity to mammalian cells. Previously we used an in silico approach to identify new potential PrAMPs from the DRAMP database. Four of these peptides, antibacterial napin, attacin-C, P9, and PP30, were each chemically assembled and characterized. Together with synthetic oncocin as a reference, each peptide was then assessed for antibacterial activity against Gram-negative/Gram-positive bacteria and for in vitro DnaK modulation activity. We observed that these peptides directly modulate DnaK activity independently of eliciting or otherwise an antibiotic effect. Based on our findings, we propose a change to our previously established PrAMP definition to remove the requirement for antimicrobial activity in isolation, leaving the following classifiers: >25% proline, modulation of DnaK AND/OR the 70S ribosome, net charge of +1 or more, produced in response to bacterial infection AND/OR with pronounced antimicrobial activity. Frontiers Media S.A. 2022-04-13 /pmc/articles/PMC9043238/ /pubmed/35494637 http://dx.doi.org/10.3389/fchem.2022.875233 Text en Copyright © 2022 Handley, Li, Welch, O’Brien-Simpson, Hossain and Wade. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Chemistry Handley, Thomas N. G. Li, Wenyi Welch, Nicholas G. O’Brien-Simpson, Neil M. Hossain, Mohammed Akhter Wade, John D. Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening |
title | Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening |
title_full | Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening |
title_fullStr | Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening |
title_full_unstemmed | Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening |
title_short | Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening |
title_sort | evaluation of potential dnak modulating proline-rich antimicrobial peptides identified by computational screening |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9043238/ https://www.ncbi.nlm.nih.gov/pubmed/35494637 http://dx.doi.org/10.3389/fchem.2022.875233 |
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