Leedale Joseph, Sharkey Kieran J, Colley Helen E, Norton Áine M, Peeney David, Mason Chantelle L, Sathish Jean G, Murdoch Craig, Sharma Parveen, Webb Steven D
EPSRC Liverpool Centre for Mathematics in Healthcare, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK.
EPSRC Liverpool Centre for Mathematics in Healthcare, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK.
iScience. 2018 Jun 29;4:84-96. doi: 10.1016/j.isci.2018.05.012. Epub 2018 May 18.
Many xenobiotics can bind to off-target receptors and cause toxicity via the dysregulation of downstream transcription factors. Identification of subsequent off-target toxicity in these chemicals has often required extensive chemical testing in animal models. An alternative, integrated in vitro/in silico approach for predicting toxic off-target functional responses is presented to refine in vitro receptor identification and reduce the burden on in vivo testing. As part of the methodology, mathematical modeling is used to mechanistically describe processes that regulate transcriptional activity following receptor-ligand binding informed by transcription factor signaling assays. Critical reactions in the signaling cascade are identified to highlight potential perturbation points in the biochemical network that can guide and optimize additional in vitro testing. A physiologically based pharmacokinetic model provides information on the timing and localization of different levels of receptor activation informing whole-body toxic potential resulting from off-target binding.
许多外源性物质可与脱靶受体结合，并通过下游转录因子的失调导致毒性。确定这些化学物质随后的脱靶毒性通常需要在动物模型中进行广泛的化学测试。本文提出了一种用于预测毒性脱靶功能反应的体外/计算机模拟相结合的替代方法，以优化体外受体鉴定并减轻体内测试的负担。作为该方法的一部分，数学模型用于从机制上描述在转录因子信号测定的指导下，受体-配体结合后调节转录活性的过程。识别信号级联中的关键反应，以突出生化网络中可能引导和优化额外体外测试的潜在扰动点。基于生理学的药代动力学模型提供了不同水平受体激活的时间和定位信息，从而了解脱靶结合导致的全身毒性潜力。
