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

Author:

Tran Vi Ngoc-NhaORCID,Shams Alireza,Ascioglu Sinan,Martinecz Antal,Liang Jingyi,Clarelli Fabrizio,Mostowy Rafal,Cohen Ted,Abel zur Wiesch Pia

Abstract

Abstract 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/.

Funder

Bill and Melinda Gates Foundation

Research Council of Norway

JPI-EC-AMR

European Molecular Biology Organization

The publication fund of UiT The Arctic University of Norway

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Extent of Antimicrobial Resistance Due to Efflux Pump Regulation;ACS Infectious Diseases;2022-10-20

2. Metabolomics in antimicrobial drug discovery;Expert Opinion on Drug Discovery;2022-08-23

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