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vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding
BACKGROUND: As antibiotic resistance creates a significant global health threat, we need not only to accelerate the development of novel antibiotics but also to develop better treatment strategies using existing drugs to improve their efficacy and prevent the selection of further resistance. We requ...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734216/ https://www.ncbi.nlm.nih.gov/pubmed/34991453 http://dx.doi.org/10.1186/s12859-021-04536-3 |
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author | Tran, Vi Ngoc-Nha Shams, Alireza Ascioglu, Sinan Martinecz, Antal Liang, Jingyi Clarelli, Fabrizio Mostowy, Rafal Cohen, Ted Abel zur Wiesch, Pia |
author_facet | Tran, Vi Ngoc-Nha Shams, Alireza Ascioglu, Sinan Martinecz, Antal Liang, Jingyi Clarelli, Fabrizio Mostowy, Rafal Cohen, Ted Abel zur Wiesch, Pia |
author_sort | Tran, Vi Ngoc-Nha |
collection | PubMed |
description | BACKGROUND: As antibiotic resistance creates a significant global health threat, we need not only to accelerate the development of novel antibiotics but also to develop better treatment strategies using existing drugs to improve their efficacy and prevent the selection of further resistance. We require new tools to rationally design dosing regimens from data collected in early phases of antibiotic and dosing development. Mathematical models such as mechanistic pharmacodynamic drug-target binding explain mechanistic details of how the given drug concentration affects its targeted bacteria. However, there are no available tools in the literature that allow non-quantitative scientists to develop computational models to simulate antibiotic-target binding and its effects on bacteria. RESULTS: In this work, we have devised an extension of a mechanistic binding-kinetic model to incorporate clinical drug concentration data. Based on the extended model, we develop a novel and interactive web-based tool that allows non-quantitative scientists to create and visualize their own computational models of bacterial antibiotic target-binding based on their considered drugs and bacteria. We also demonstrate how Rifampicin affects bacterial populations of Tuberculosis bacteria using our vCOMBAT tool. CONCLUSIONS: The vCOMBAT online tool is publicly available at https://combat-bacteria.org/. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04536-3. |
format | Online Article Text |
id | pubmed-8734216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87342162022-01-07 vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding Tran, Vi Ngoc-Nha Shams, Alireza Ascioglu, Sinan Martinecz, Antal Liang, Jingyi Clarelli, Fabrizio Mostowy, Rafal Cohen, Ted Abel zur Wiesch, Pia BMC Bioinformatics Software BACKGROUND: As antibiotic resistance creates a significant global health threat, we need not only to accelerate the development of novel antibiotics but also to develop better treatment strategies using existing drugs to improve their efficacy and prevent the selection of further resistance. We require new tools to rationally design dosing regimens from data collected in early phases of antibiotic and dosing development. Mathematical models such as mechanistic pharmacodynamic drug-target binding explain mechanistic details of how the given drug concentration affects its targeted bacteria. However, there are no available tools in the literature that allow non-quantitative scientists to develop computational models to simulate antibiotic-target binding and its effects on bacteria. RESULTS: In this work, we have devised an extension of a mechanistic binding-kinetic model to incorporate clinical drug concentration data. Based on the extended model, we develop a novel and interactive web-based tool that allows non-quantitative scientists to create and visualize their own computational models of bacterial antibiotic target-binding based on their considered drugs and bacteria. We also demonstrate how Rifampicin affects bacterial populations of Tuberculosis bacteria using our vCOMBAT tool. CONCLUSIONS: The vCOMBAT online tool is publicly available at https://combat-bacteria.org/. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04536-3. BioMed Central 2022-01-06 /pmc/articles/PMC8734216/ /pubmed/34991453 http://dx.doi.org/10.1186/s12859-021-04536-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Tran, Vi Ngoc-Nha Shams, Alireza Ascioglu, Sinan Martinecz, Antal Liang, Jingyi Clarelli, Fabrizio Mostowy, Rafal Cohen, Ted Abel zur Wiesch, Pia vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding |
title | vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding |
title_full | vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding |
title_fullStr | vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding |
title_full_unstemmed | vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding |
title_short | vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding |
title_sort | vcombat: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8734216/ https://www.ncbi.nlm.nih.gov/pubmed/34991453 http://dx.doi.org/10.1186/s12859-021-04536-3 |
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