Watson Ian A, Wang Jibo, Nicolaou Christos A
Discovery Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, 46285, USA.
J Cheminform. 2019 Jan 3;11(1):1. doi: 10.1186/s13321-018-0323-6.
The need for synthetic route design arises frequently in discovery-oriented chemistry organizations. While traditionally finding solutions to this problem has been the domain of human experts, several computational approaches, aided by the algorithmic advances and the availability of large reaction collections, have recently been reported. Herein we present our own implementation of a retrosynthetic analysis method and demonstrate its capabilities in an attempt to identify synthetic routes for a collection of approved drugs. Our results indicate that the method, leveraging on reaction transformation rules learned from a large patent reaction dataset, can identify multiple theoretically feasible synthetic routes and, thus, support research chemist everyday efforts.
在以发现为导向的化学机构中，合成路线设计的需求经常出现。虽然传统上解决这个问题一直是人类专家的领域，但最近有报道称，在算法进步和大量反应集的可用性的辅助下，出现了几种计算方法。在此，我们展示了我们自己对逆合成分析方法的实现，并展示了其能力，试图为一批已批准的药物确定合成路线。我们的结果表明，该方法利用从大型专利反应数据集中学习到的反应转化规则，可以识别多个理论上可行的合成路线，从而支持研究化学家的日常工作。
