Efficient measurement and factorization of high-order drug interactions in Mycobacterium tuberculosis.
Efficient measurement and factorization of high-order drug interactions in Mycobacterium tuberculosis.
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DOI：
10.1126/sciadv.1701881
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发表时间：
2017-10
期刊：
影响因子：
13.6
通讯作者：
Aldridge BB
中科院分区：
文献类型：
--
作者：
Cokol M;Kuru N;Bicak E;Larkins-Ford J;Aldridge BB
药物剂量组合的几何优化采样使得能够系统地识别高阶药物协同作用。三种或三种以上药物的组合用于治疗许多疾病，包括结核病。因此，重要的是要了解协同或拮抗药物相互作用如何影响联合治疗的疗效。然而，由于缺乏有效的测量方法和分析解释的理论框架，我们对高阶药物相互作用的理解是有限的。我们开发了一种有效的实验采样和评分方法[n向药物相互作用的对角测量（DiaMOND）]，以测量任何数量药物组合的药物相互作用。DiaMOND提供了一种有效的替代棋盘测定法，棋盘测定法通常用于测量药物相互作用。我们建立了一个几何框架，将高阶药物相互作用分解为低阶组分，从而建立了如何使用低阶测量来预测高阶相互作用的路线图。我们的框架是一个广义Loewe加性模型的高阶药物相互作用。使用DiaMOND，我们确定并分析了协同和拮抗抗生素组合对结核分枝杆菌。DiaMOND对高阶药物相互作用的有效测量和因子分解广泛适用于其他细胞类型和疾病模型。
Geometrically optimized sampling of drug-dose combinations enables systematic identification of high-order drug synergies. Combinations of three or more drugs are used to treat many diseases, including tuberculosis. Thus, it is important to understand how synergistic or antagonistic drug interactions affect the efficacy of combination therapies. However, our understanding of high-order drug interactions is limited because of the lack of both efficient measurement methods and theoretical framework for analysis and interpretation. We developed an efficient experimental sampling and scoring method [diagonal measurement of n-way drug interactions (DiaMOND)] to measure drug interactions for combinations of any number of drugs. DiaMOND provides an efficient alternative to checkerboard assays, which are commonly used to measure drug interactions. We established a geometric framework to factorize high-order drug interactions into lower-order components, thereby establishing a road map of how to use lower-order measurements to predict high-order interactions. Our framework is a generalized Loewe additivity model for high-order drug interactions. Using DiaMOND, we identified and analyzed synergistic and antagonistic antibiotic combinations against Mycobacterium tuberculosis. Efficient measurement and factorization of high-order drug interactions by DiaMOND are broadly applicable to other cell types and disease models.
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DOI：
10.1126/science.aad3292
发表时间：
2016-01-01
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Baym M;Stone LK;Kishony R
通讯作者：
Kishony R
DOI：
10.1093/cid/ciw474
发表时间：
2016-11-01
期刊：
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
影响因子：
--
作者：
Deshpande D;Srivastava S;Nuermberger E;Pasipanodya JG;Swaminathan S;Gumbo T
通讯作者：
Gumbo T
影响因子：
2.6
作者：
Foucquier, Julie;Guedj, Mickael
通讯作者：
Guedj, Mickael
影响因子：
4.9
作者：
Almeida, Deepak;Nuermberger, Eric;Grosset, Jacques
通讯作者：
Grosset, Jacques
影响因子：
168.9
作者：
Dawson, Rodney;Diacon, Andreas H.;Mendel, Carl M.
通讯作者：
Mendel, Carl M.