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.

中文翻译：

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一种后综合分析算法的实现。

在以发现为导向的化学组织中，经常会出现对合成路线设计的需求。尽管传统上一直在寻找解决该问题的方法，这一直是人类专家的工作领域，但最近已报道了借助算法的进步和大量反应集合的可用性的几种计算方法。在这里，我们介绍了我们自己的逆合成分析方法的实现，并展示了其功能，旨在为批准的药物鉴定合成途径。我们的结果表明，该方法利用从大型专利反应数据集中获悉的反应转化规则，可以确定多种理论上可行的合成路线，从而为研究化学家的日常工作提供支持。