Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion

Abstract Combinations of more than two drugs are routinely used for the treatment of pathogens and tumors. High-order combinations may be chosen due to their non-overlapping resistance mechanisms or for favorable drug interactions. Synergistic/antagonistic interactions occur when the combination has...

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Autores principales:	Kaan Yilancioglu, Murat Cokol
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/21d8f3fd5d3645beafda8dbc82d808e3
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spelling	oai:doaj.org-article:21d8f3fd5d3645beafda8dbc82d808e32021-12-02T15:09:00ZDesign of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion10.1038/s41598-019-48410-y2045-2322https://doaj.org/article/21d8f3fd5d3645beafda8dbc82d808e32019-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-019-48410-yhttps://doaj.org/toc/2045-2322Abstract Combinations of more than two drugs are routinely used for the treatment of pathogens and tumors. High-order combinations may be chosen due to their non-overlapping resistance mechanisms or for favorable drug interactions. Synergistic/antagonistic interactions occur when the combination has a higher/lower effect than the sum of individual drug effects. The standard treatment of Mycobacterium tuberculosis (Mtb) is an additive cocktail of three drugs which have different targets. Herein, we experimentally measured all 190 pairwise interactions among 20 antibiotics against Mtb growth. We used the pairwise interaction data to rank all possible high-order combinations by strength of synergy/antagonism. We used drug interaction profile correlation as a proxy for drug similarity to establish exclusion criteria for ideal combination therapies. Using this ranking and exclusion design (R/ED) framework, we modeled ways to improve the standard 3-drug combination with the addition of new drugs. We applied this framework to find the best 4-drug combinations against drug-resistant Mtb by adding new exclusion criteria to R/ED. Finally, we modeled alternating 2-order combinations as a cycling treatment and found optimized regimens significantly reduced the overall effective dose. R/ED provides an adaptable framework for the design of high-order drug combinations against any pathogen or tumor.Kaan YilanciogluMurat CokolNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 9, Iss 1, Pp 1-11 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kaan Yilancioglu Murat Cokol Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion
description	Abstract Combinations of more than two drugs are routinely used for the treatment of pathogens and tumors. High-order combinations may be chosen due to their non-overlapping resistance mechanisms or for favorable drug interactions. Synergistic/antagonistic interactions occur when the combination has a higher/lower effect than the sum of individual drug effects. The standard treatment of Mycobacterium tuberculosis (Mtb) is an additive cocktail of three drugs which have different targets. Herein, we experimentally measured all 190 pairwise interactions among 20 antibiotics against Mtb growth. We used the pairwise interaction data to rank all possible high-order combinations by strength of synergy/antagonism. We used drug interaction profile correlation as a proxy for drug similarity to establish exclusion criteria for ideal combination therapies. Using this ranking and exclusion design (R/ED) framework, we modeled ways to improve the standard 3-drug combination with the addition of new drugs. We applied this framework to find the best 4-drug combinations against drug-resistant Mtb by adding new exclusion criteria to R/ED. Finally, we modeled alternating 2-order combinations as a cycling treatment and found optimized regimens significantly reduced the overall effective dose. R/ED provides an adaptable framework for the design of high-order drug combinations against any pathogen or tumor.
format	article
author	Kaan Yilancioglu Murat Cokol
author_facet	Kaan Yilancioglu Murat Cokol
author_sort	Kaan Yilancioglu
title	Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion
title_short	Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion
title_full	Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion
title_fullStr	Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion
title_full_unstemmed	Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion
title_sort	design of high-order antibiotic combinations against m. tuberculosis by ranking and exclusion
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/21d8f3fd5d3645beafda8dbc82d808e3
work_keys_str_mv	AT kaanyilancioglu designofhighorderantibioticcombinationsagainstmtuberculosisbyrankingandexclusion AT muratcokol designofhighorderantibioticcombinationsagainstmtuberculosisbyrankingandexclusion
_version_	1718387925534638080

Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion

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