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首页> 外文期刊>NPJ systems biology and applications. >Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation
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Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation

机译:将基因组规模的代谢网络整合到全身PBPK模型中,显示药物诱导的代谢扰动的表型特异性病例

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摘要

Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.
机译:药物引起的内源性代谢网络扰动是细胞毒性的潜在根本原因。因此,对药物治疗过程中此类不良副作用的机械理解对于患者安全至关重要。对此类药物引起的损伤的全面评估需要同时考虑全身的药物暴露和细胞水平的生化反应。我们在这里提出了一种计算的多尺度工作流程,通过异种生物代谢的共享反应,结合了基于全身生理学的药代动力学(PBPK)模型和器官特异性基因组尺度的代谢网络(GSMN)模型。说明了拟议的工作流程对异烟肼的治疗性,异烟肼是一种针对结核分枝杆菌的一线抗菌剂,已知会引起特异药物性肝损伤(DILI)。我们将人肝的GSMN模型与异烟肼的N-乙酰基转移酶2(NAT2)-表型特异性PBPK模型结合在一起。 PBPB-GSMN组合模型定量描述了异烟肼给药后异烟肼的药代动力学以及细胞内反应以及人肝脏中代谢组代谢的变化。值得注意的是,用PBPK-GSMN模型鉴定的细胞内和细胞外反应与实验和临床发现一致。而且,药物诱导的代谢扰动以表型依赖性方式在代谢网络中分布和减弱。我们的模拟结果表明,必须同时考虑全身的药物药代动力学和细胞水平的代谢,才能在患者水平上解释药物引起的损伤。拟议的工作流程扩展了我们对不良事件背后的生化机制的机械理解,并可在将来用于预防药物引起的伤害。

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