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Dimensionless parameter predicts bacterial prodrug success
Understanding mechanisms of antibiotic failure is foundational to combating the growing threat of multidrug‐resistant bacteria. Prodrugs—which are converted into a pharmacologically active compound after administration—represent a growing class of therapeutics for treating bacterial infections but a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8744131/ https://www.ncbi.nlm.nih.gov/pubmed/35005851 http://dx.doi.org/10.15252/msb.202110495 |
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author | Holt, Brandon Alexander Tuttle, McKenzie Xu, Yilin Su, Melanie Røise, Joachim J Wang, Xioajian Murthy, Niren Kwong, Gabriel A |
author_facet | Holt, Brandon Alexander Tuttle, McKenzie Xu, Yilin Su, Melanie Røise, Joachim J Wang, Xioajian Murthy, Niren Kwong, Gabriel A |
author_sort | Holt, Brandon Alexander |
collection | PubMed |
description | Understanding mechanisms of antibiotic failure is foundational to combating the growing threat of multidrug‐resistant bacteria. Prodrugs—which are converted into a pharmacologically active compound after administration—represent a growing class of therapeutics for treating bacterial infections but are understudied in the context of antibiotic failure. We hypothesize that strategies that rely on pathogen‐specific pathways for prodrug conversion are susceptible to competing rates of prodrug activation and bacterial replication, which could lead to treatment escape and failure. Here, we construct a mathematical model of prodrug kinetics to predict rate‐dependent conditions under which bacteria escape prodrug treatment. From this model, we derive a dimensionless parameter we call the Bacterial Advantage Heuristic (BAH) that predicts the transition between prodrug escape and successful treatment across a range of time scales (1–10(4) h), bacterial carrying capacities (5 × 10(4)–10(5) CFU/µl), and Michaelis constants (K(M) = 0.747–7.47 mM). To verify these predictions in vitro, we use two models of bacteria‐prodrug competition: (i) an antimicrobial peptide hairpin that is enzymatically activated by bacterial surface proteases and (ii) a thiomaltose‐conjugated trimethoprim that is internalized by bacterial maltodextrin transporters and hydrolyzed by free thiols. We observe that prodrug failure occurs at BAH values above the same critical threshold predicted by the model. Furthermore, we demonstrate two examples of how failing prodrugs can be rescued by decreasing the BAH below the critical threshold via (i) substrate design and (ii) nutrient control. We envision such dimensionless parameters serving as supportive pharmacokinetic quantities that guide the design and administration of prodrug therapeutics. |
format | Online Article Text |
id | pubmed-8744131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87441312022-01-13 Dimensionless parameter predicts bacterial prodrug success Holt, Brandon Alexander Tuttle, McKenzie Xu, Yilin Su, Melanie Røise, Joachim J Wang, Xioajian Murthy, Niren Kwong, Gabriel A Mol Syst Biol Articles Understanding mechanisms of antibiotic failure is foundational to combating the growing threat of multidrug‐resistant bacteria. Prodrugs—which are converted into a pharmacologically active compound after administration—represent a growing class of therapeutics for treating bacterial infections but are understudied in the context of antibiotic failure. We hypothesize that strategies that rely on pathogen‐specific pathways for prodrug conversion are susceptible to competing rates of prodrug activation and bacterial replication, which could lead to treatment escape and failure. Here, we construct a mathematical model of prodrug kinetics to predict rate‐dependent conditions under which bacteria escape prodrug treatment. From this model, we derive a dimensionless parameter we call the Bacterial Advantage Heuristic (BAH) that predicts the transition between prodrug escape and successful treatment across a range of time scales (1–10(4) h), bacterial carrying capacities (5 × 10(4)–10(5) CFU/µl), and Michaelis constants (K(M) = 0.747–7.47 mM). To verify these predictions in vitro, we use two models of bacteria‐prodrug competition: (i) an antimicrobial peptide hairpin that is enzymatically activated by bacterial surface proteases and (ii) a thiomaltose‐conjugated trimethoprim that is internalized by bacterial maltodextrin transporters and hydrolyzed by free thiols. We observe that prodrug failure occurs at BAH values above the same critical threshold predicted by the model. Furthermore, we demonstrate two examples of how failing prodrugs can be rescued by decreasing the BAH below the critical threshold via (i) substrate design and (ii) nutrient control. We envision such dimensionless parameters serving as supportive pharmacokinetic quantities that guide the design and administration of prodrug therapeutics. John Wiley and Sons Inc. 2022-01-10 /pmc/articles/PMC8744131/ /pubmed/35005851 http://dx.doi.org/10.15252/msb.202110495 Text en © 2022 The Authors. Published under the terms of the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Holt, Brandon Alexander Tuttle, McKenzie Xu, Yilin Su, Melanie Røise, Joachim J Wang, Xioajian Murthy, Niren Kwong, Gabriel A Dimensionless parameter predicts bacterial prodrug success |
title | Dimensionless parameter predicts bacterial prodrug success |
title_full | Dimensionless parameter predicts bacterial prodrug success |
title_fullStr | Dimensionless parameter predicts bacterial prodrug success |
title_full_unstemmed | Dimensionless parameter predicts bacterial prodrug success |
title_short | Dimensionless parameter predicts bacterial prodrug success |
title_sort | dimensionless parameter predicts bacterial prodrug success |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8744131/ https://www.ncbi.nlm.nih.gov/pubmed/35005851 http://dx.doi.org/10.15252/msb.202110495 |
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