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vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding

Permanent lenke
https://hdl.handle.net/10037/25062
DOI
https://doi.org/10.1186/s12859-021-04536-3
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article.pdf (1.752Mb)
Publisert versjon (PDF)
Dato
2022-01-06
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Forfatter
Tran, Vi Ngoc-Nha; Shams, Alireza; Ascioglu, Sinan; Martinecz, Antal; Liang, Jingyi; Clarelli, Fabrizio; Mostowy, Rafal; Cohen, Ted; Abel zur Wiesch, Pia
Sammendrag
Background: As antibiotic resistance creates a signifcant 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 efcacy 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 afects its targeted bacteria. However, there are no available tools in the literature that allow non-quantita‑ tive scientists to develop computational models to simulate antibiotic-target binding and its efects 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 afects bacterial populations of Tuberculosis bacteria using our vCOM‑ BAT tool.

Conclusions: The vCOMBAT online tool is publicly available at https://combat-bacte ria.org/.

Forlag
BMC
Sitering
Tran VNN, Shams A, Ascioglu, Martinecz A, Liang J, Clarelli F, Mostowy R, Cohen T, Abel zur Wiesch P. vCOMBAT: a novel tool to create and visualize a computational model of bacterial antibiotic target-binding. BMC Bioinformatics. 2022;23(1):1-15
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  • Artikler, rapporter og annet (farmasi) [394]
Copyright 2021 The Author(s)

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