Hepatic metabolic stability is a key pharmacokinetic parameter in drug discovery. Metabolic stability is usually assessed in microsomal fractions and only the best compounds progress in the drug discovery process. A high-throughput single time point substrate depletion assay in rat liver microsomes (RLM) is employed at the National Center for Advancing Translational Sciences. Between 2012 and 2020, RLM stability data was generated for ~ 24,000 compounds from more than 250 projects that cover a wide range of pharmacological targets and cellular pathways. Although a crucial endpoint, little or no data exists in the public domain. In this study, computational models were developed for predicting RLM stability using different machine learning methods. In addition, a retrospective time-split validation was performed, and local models were built for projects that performed poorly with global models. Further analysis revealed inherent medicinal chemistry knowledge potentially useful to chemists in the pursuit of synthesizing metabolically stable compounds. In addition, we deposited experimental data for ~ 2500 compounds in the PubChem bioassay database (AID: 1508591). The global prediction models are made publicly accessible (https://opendata.ncats.nih.gov/adme). This is to the best of our knowledge, the first publicly available RLM prediction model built using high-quality data generated at a single laboratory.

肝脏代谢稳定性是药物发现的关键药代动力学参数。代谢稳定性通常以微粒体部分进行评估，只有最好的化合物才能在药物发现过程中取得进展。国家推进转化科学中心采用大鼠肝微粒体 (RLM) 中的高通量单时间点底物消耗测定法。在 2012 年至 2020 年间，为来自 250 多个项目的约 24,000 种化合物生成了 RLM 稳定性数据，这些项目涵盖了广泛的药理学靶点和细胞途径。尽管是一个关键端点，但公共领域中很少或根本没有数据。在这项研究中，开发了计算模型，用于使用不同的机器学习方法预测 RLM 稳定性。此外，还进行了回顾性时间分割验证，本地模型是为在全球模型中表现不佳的项目构建的。进一步的分析揭示了内在的药物化学知识可能对化学家在合成代谢稳定的化合物方面有用。此外，我们在 PubChem 生物测定数据库 (AID: 1508591) 中保存了约 2500 种化合物的实验数据。全球预测模型可公开访问 (https://opendata.ncats.nih.gov/adme)。据我们所知，这是第一个使用在单个实验室生成的高质量数据构建的公开可用的 RLM 预测模型。我们在 PubChem 生物测定数据库 (AID: 1508591) 中保存了约 2500 种化合物的实验数据。全球预测模型可公开访问 (https://opendata.ncats.nih.gov/adme)。据我们所知，这是第一个使用在单个实验室生成的高质量数据构建的公开可用的 RLM 预测模型。我们在 PubChem 生物测定数据库 (AID: 1508591) 中保存了约 2500 种化合物的实验数据。全球预测模型可公开访问 (https://opendata.ncats.nih.gov/adme)。据我们所知，这是第一个使用在单个实验室生成的高质量数据构建的公开可用的 RLM 预测模型。