针对小分子的药理学目标介导药物排放 (TMDD) 的目标丰富性 - 一种蛋白质学方法
Min Xu1, Xuanzhen Yuan1, Peizhi Li1
1Department of Pharmaceutical Sciences and Experimental Therapeutics, College of Pharmacy, University of Iowa, 115 S Grand Ave, Iowa City, Iowa, 52242, USA.
目标介导药物排放 (TMDD) 导致非线性药理动力学 (PK),当药物点具有特定的能力时. 使用蛋白质组学量化目标量有助于预测TMDD,有助于药物开发.
科学领域:
- 药理动力学和药物新陈代谢
- 蛋白质组学和定量生物学
- 药物发现和开发 药物发现和开发
背景情况:
- 非线性药理动力学 (PK),特别是向中介药物排放 (TMDD),在小分子药物中越来越多地观察到.
- 一种 TMDD 类效应,以类似的非线性 PK 为特征,已在 11β-基固醇脱酶 1 型 (11β-HSD1),单胺氧化酶 B 型 (MAO-B) 和可溶性环氧化酶 (sEH) 抑制剂中观察到.
研究的目的:
- 调查这一假设,即当药物目标具有特定的,可量化的能力时,TMDD类效应会发生.
- 建立与可观测的TMDD相关的目标丰度的预测范围.
主要方法:
- 利用基于质谱 (MS) 的全球蛋白质组学方法量化11β-HSD1,MAO-B和sEH在各种组织和物种中的绝对蛋白质度.
- 计算了这些关键药物标在人体组织中的总摩尔量.
主要成果:
- 估计11β-HSD1,MAO-B和sEH在人体中的目标量分别为大约4994,4629和4137nmol.
- 这些可比的丰度水平表明,对于1000-10000nmol范围内的目标,TMDD可能很明显.
- 这个范围与400g/mol化合物的1-10mg剂量的非线性PK相关.
结论:
- 对绝对目标容量的早期量化对于预测和理解由TMDD驱动的非线性PK至关重要.
- 这些发现为识别早期药物开发过程中的潜在TMDD负债提供了一个框架.
- 描述的蛋白质组学方法为评估药理学研究中的目标能力提供了有价值的工具.
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