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寻找立体控制反应的相关逆合成切断

Finding Relevant Retrosynthetic Disconnections for Stereocontrolled Reactions.

作者信息

Wiest Olaf, Bauer Christoph, Helquist Paul, Norrby Per-Ola, Genheden Samuel

机构信息

Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States.

Data Science and Modelling, Pharmaceutical Sciences, R&D, AstraZeneca, Gothenburg, Pepparedsleden 1, SE-431 83 Mölndal, Sweden.

出版信息

J Chem Inf Model. 2024 Aug 12;64(15):5796-5805. doi: 10.1021/acs.jcim.4c00370. Epub 2024 Jul 12.

Abstract

Machine learning-driven computer-aided synthesis planning (CASP) tools have become important tools for idea generation in the design of complex molecule synthesis but do not adequately address the stereochemical features of the target compounds. A novel approach to automated extraction of templates used in CASP that includes stereochemical information included in the US Patent and Trademark Office (USPTO) and an internal AstraZeneca database containing reactions from Reaxys, Pistachio, and AstraZeneca electronic lab notebooks is implemented in the freely available AiZynthFinder software. Three hundred sixty-seven templates covering reagent- and substrate-controlled as well as stereospecific reactions were extracted from the USPTO, while 20,724 templates were from the AstraZeneca database. The performance of these templates in multistep CASP is evaluated for 936 targets from the ChEMBL database and an in-house selection of 791 AZ designs. The potential and limitations are discussed for four case studies from ChEMBL and examples of FDA-approved drugs.

摘要

机器学习驱动的计算机辅助合成规划(CASP)工具已成为复杂分子合成设计中产生想法的重要工具,但并未充分解决目标化合物的立体化学特征。一种用于自动提取CASP中使用的模板的新方法得以实现,该方法包括美国专利商标局(USPTO)中包含的立体化学信息以及阿斯利康内部数据库,该数据库包含来自Reaxys、Pistachio和阿斯利康电子实验室笔记本的反应,该方法在免费提供的AiZynthFinder软件中得以实施。从USPTO中提取了367个涵盖试剂和底物控制以及立体特异性反应的模板,而从阿斯利康数据库中提取了20724个模板。针对来自ChEMBL数据库的936个目标以及791个阿斯利康内部设计的选择,评估了这些模板在多步CASP中的性能。针对来自ChEMBL的四个案例研究以及FDA批准药物的示例,讨论了其潜力和局限性。

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