Medivir, Lunastigen 7, 141 22 Huddinge, Sweden.
Department of Laboratory Medicine, Huddinge Universitetssjukhus, 141 57.
Future Med Chem. 2018 Jul 1;10(13):1575-1588. doi: 10.4155/fmc-2017-0323. Epub 2018 Jun 28.
Metabolic stability is an important property of drug candidates and pharmaceutical companies often have human liver microsomal (HLM) data for a large number of molecules, enabling development of global quantitative structure-activity relationship models.
This study describes a strategy for building a global HLM quantitative structure-activity relationship model, applicable also to datasets of limited size. By using external congeneric test sets, a realistic description of the performance in the future applied setting and a reliable prediction confidence method is obtained.
The limited ability of the HLM model to generalize in chemical space to show the importance of internal model development and continuous updating of global HLM models, as well as the importance of a validated prediction confidence method.
代谢稳定性是候选药物的一个重要性质，制药公司通常拥有大量分子的人肝微粒体（HLM）数据，从而能够开发全球定量构效关系模型。
本研究描述了一种构建全球 HLM 定量构效关系模型的策略，该策略也适用于规模有限的数据集。通过使用外部同源测试集，获得了在未来应用环境中的性能的现实描述和可靠的预测置信度方法。
HLM 模型在化学空间中的概括能力有限，这表明内部模型开发和全球 HLM 模型的持续更新的重要性，以及验证预测置信度方法的重要性。
