Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94501, United States.
GlaxoSmithKline, LLC 1250 S Collegeville Rd, Collegeville, Pennsylvania 19426, United States.
J Chem Inf Model. 2021 Feb 22;61(2):587-602. doi: 10.1021/acs.jcim.0c00950. Epub 2021 Jan 27.
Cholestatic liver injury is frequently associated with drug inhibition of bile salt transporters, such as the bile salt export pump (BSEP). Reliable models to predict BSEP inhibition directly from chemical structures would significantly reduce costs during drug discovery and could help avoid injury to patients. We report our development of classification and regression models for BSEP inhibition with substantially improved performance over previously published models. We assessed the performance effects of different methods of chemical featurization, data set partitioning, and class labeling and identified the methods producing models that generalized best to novel chemical entities.
胆汁淤积性肝损伤通常与药物抑制胆盐转运体有关，如胆汁盐输出泵（BSEP）。能够直接从化学结构预测 BSEP 抑制的可靠模型将显著降低药物发现过程中的成本，并有助于避免对患者造成伤害。我们报告了分类和回归模型的发展，用于 BSEP 抑制，其性能明显优于以前发表的模型。我们评估了不同化学特征化方法、数据集划分和类别标记的性能效果，并确定了产生对新化学实体具有最佳泛化能力的模型的方法。
