Sharma Sheena, Singh Dilip K, Mettu Vijay S, Yue Guihua, Ahire Deepak, Basit Abdul, Heyward Scott, Prasad Bhagwat
College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington 99202, United States.
BioIVT, Baltimore, Maryland 21227, United States.
Mol Pharm. 2023 Mar 6;20(3):1737-1749. doi: 10.1021/acs.molpharmaceut.2c00950. Epub 2023 Feb 15.
Rats are extensively used as a preclinical model for assessing drug pharmacokinetics (PK) and tissue distribution; however, successful translation of the rat data requires information on the differences in drug metabolism and transport mechanisms between rats and humans. To partly fill this knowledge gap, we quantified clinically relevant drug-metabolizing enzymes and transporters (DMETs) in the liver and different intestinal segments of Sprague-Dawley rats. The levels of DMET proteins in rats were quantified using the global proteomics-based total protein approach (TPA) and targeted proteomics. The abundance of the major DMET proteins was largely comparable using quantitative global and targeted proteomics. However, global proteomics-based TPA was able to detect and quantify a comprehensive list of 66 DMET proteins in the liver and 37 DMET proteins in the intestinal segments of SD rats without the need for peptide standards. Cytochrome P450 (Cyp) and UDP-glycosyltransferase (Ugt) enzymes were mainly detected in the liver with the abundance ranging from 8 to 6502 and 74 to 2558 pmol/g tissue. P-gp abundance was higher in the intestine (124.1 pmol/g) as compared to that in the liver (26.6 pmol/g) using the targeted analysis. Breast cancer resistance protein (Bcrp) was most abundant in the intestinal segments, whereas organic anion transporting polypeptides (Oatp) 1a1, 1a4, 1b2, and 2a1 and multidrug resistance proteins (Mrp) 2 and 6 were predominantly detected in the liver. To demonstrate the utility of these data, we modeled digoxin PK by integrating protein abundance of P-gp and Cyp3a2 into a physiologically based PK (PBPK) model constructed using PK-Sim software. The model was able to reliably predict the systemic as well as tissue concentrations of digoxin in rats. These findings suggest that proteomics-informed PBPK models in preclinical species can allow mechanistic PK predictions in animal models including tissue drug concentrations.
大鼠被广泛用作评估药物药代动力学（PK）和组织分布的临床前模型；然而，要成功将大鼠数据转化应用，需要了解大鼠和人类在药物代谢及转运机制方面的差异。为部分填补这一知识空白，我们对斯普拉格 - 道利大鼠的肝脏和不同肠段中临床相关的药物代谢酶和转运蛋白（DMETs）进行了定量分析。使用基于全局蛋白质组学的总蛋白方法（TPA）和靶向蛋白质组学对大鼠体内DMET蛋白的水平进行了定量。使用定量全局蛋白质组学和靶向蛋白质组学，主要DMET蛋白的丰度在很大程度上具有可比性。然而，基于全局蛋白质组学的TPA能够检测并定量出SD大鼠肝脏中的66种DMET蛋白以及肠段中的37种DMET蛋白，且无需肽标准品。细胞色素P450（Cyp）和尿苷二磷酸葡萄糖基转移酶（Ugt）酶主要在肝脏中检测到丰度范围为8至6502 pmol/g组织和74至2558 pmol/g组织。使用靶向分析，与肝脏中的P - gp丰度（26.6 pmol/g）相比，肠道中的P - gp丰度更高（124.1 pmol/g）。乳腺癌耐药蛋白（Bcrp）在肠段中最为丰富，而有机阴离子转运多肽（Oatp）1a1、1a4、1b2和2a1以及多药耐药蛋白（Mrp）2和6主要在肝脏中检测到。为证明这些数据的实用性，我们通过将P - gp和Cyp3a2的蛋白丰度整合到使用PK - Sim软件构建的基于生理的PK（PBPK）模型中，对洋地黄毒苷的PK进行了建模。该模型能够可靠地预测大鼠体内洋地黄毒苷的全身浓度以及组织浓度。这些发现表明，临床前物种中基于蛋白质组学的PBPK模型能够在动物模型中进行包括组织药物浓度在内的机制性PK预测。
