CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration
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Journal of Cheminformatics Open Access
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration Ryosuke Shibukawa1† , Shoichi Ishida2† , Kazuki Yoshizoe3, Kunihiro Wasa4, Kiyosei Takasu2 , Yasushi Okuno5,6 , Kei Terayama3,5,6,7* and Koji Tsuda1,3,8*
Abstract In computer-assisted synthesis planning (CASP) programs, providing as many chemical synthetic routes as possible is essential for considering optimal and alternative routes in a chemical reaction network. As the majority of CASP programs have been designed to provide one or a few optimal routes, it is likely that the desired one will not be included. To avoid this, an exact algorithm that lists possible synthetic routes within the chemical reaction network is required, alongside a recommendation of synthetic routes that meet specified criteria based on the chemist’s objectives. Herein, we propose a chemical-reaction-network-based synthetic route recommendation framework called “CompRet” with a mathematically guaranteed enumeration algorithm. In a preliminary experiment, CompRet was shown to successfully provide alternative routes for a known antihistaminic drug, cetirizine. CompRet is expected to promote desirable enumeration-based chemical synthesis searches and aid the development of an interactive CASP framework for chemists. Keywords: Retosynthesis, Enumeration, Computer-assisted synthesis planning Introduction Since the 1960s, several researchers have proposed computer-assisted chemical synthetic route designs. Various computer-assisted synthesis planning (CASP) programs have been developed to assist synthetic organic chemists in their work [1–3]. While expert systems and knowledge-based programs were the primary focus of CASP during the early stages [4–8], recent breakthroughs in the field of deep learning and widespread *Correspondence: terayama@yokohama‑cu.ac.jp; [email protected]‑tokyo.ac.jp † Ryosuke Shibukawa and Shoichi Ishida Contributed equally 7 Graduate School of Medical Life Science, Yokohama City University, Kanagawa, Japan 8 Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Kyoto, Japan Full list of author information is available at the end of the article
availability of reaction datasets have accelerated its development [9–17]. In particular, data-driven approaches have received attention across research fields [18–21]. These approaches for multi-step synthesis planning have shown outstanding performance at every stage, and more recently, they have provided realistic and preferable synthetic routes. The pioneers of CASP, Corey and Wipke, stated the following requirements related to the above strategy in their paper [2]: the program needs to provide as many useful routes as possible, chemists can decide the depth of search or analysis of the synthetic route, and the given routes are evaluated by the chemists. As discussed above, several CASP approaches have been developed; however, the majority of
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