Wan Hong, Ahman Madeleine, Holmén Anders G
Lead Generation, DMPK and Physical Chemistry, AstraZeneca R&D Mölndal, SE-431 83 Mölndal, Sweden.
J Med Chem. 2009 Mar 26;52(6):1693-700. doi: 10.1021/jm801441s.
In CNS drug discovery, knowledge of drug-tissue binding is essential for a better understanding of brain penetration by assessing unbound brain to plasma ratio as well as pharmacokinetics (PK) and pharmacodynamics (PD) relationship by relating free drug concentration to pharmacological effect in target tissues. In this work, we present a novel microemulsion based capillary electrophoresis (CE) method that enables coupling microemulsion electrokinetic chromatography (MEEKC) to mass spectrometry (MS) for prediction of biopartitioning of CNS drugs in brain tissue. Compared to LC retention based lipophilicity and calculated lipophilicity, a significantly improved correlation between the LogP values obtained from MEEKC retention factors and fraction unbound (fu) in brain tissue was observed for a training set of structurally diverse CNS drugs as well as for a test set of new chemical entities (NCEs). The current online CE/MS/MEEKC technique can also be a potential approach for lipophilicity screening amenable for highly predictive of other ADME-Tox properties of NCEs using the MEEKC partitioning coefficient as a relevant descriptor.
在中枢神经系统(CNS)药物研发中,了解药物与组织的结合对于通过评估未结合的脑血浆比来更好地理解脑渗透性,以及通过将游离药物浓度与靶组织中的药理效应相关联来了解药代动力学(PK)和药效学(PD)关系至关重要。在这项工作中,我们提出了一种基于微乳液的新型毛细管电泳(CE)方法,该方法能够将微乳液电动色谱(MEEKC)与质谱(MS)联用,以预测中枢神经系统药物在脑组织中的生物分配。与基于液相色谱保留的亲脂性和计算得到的亲脂性相比,对于一组结构多样的中枢神经系统药物训练集以及一组新化学实体(NCEs)测试集,观察到从MEEKC保留因子获得的LogP值与脑组织中未结合分数(fu)之间的相关性显著提高。当前的在线CE/MS/MEEKC技术也可能是一种亲脂性筛选的潜在方法,适用于使用MEEKC分配系数作为相关描述符来高度预测NCEs的其他药物代谢动力学-药物处置-毒性(ADME-Tox)性质。