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. 2023 Sep 11;63(17):5484-5495.
doi: 10.1021/acs.jcim.3c00491. Epub 2023 Aug 27.

SynRoute: A Retrosynthetic Planning Software

Mario Latendresse  1 , Jeremiah P Malerich  1 , James Herson  1 , Markus Krummenacker  1 , Judy Szeto  1 , Vi-Anh Vu  1 , Nathan Collins  1 , Peter B Madrid  1
Affiliations

SynRoute: A Retrosynthetic Planning Software

Mario Latendresse et al. J Chem Inf Model. .

Abstract

Computer-assisted synthetic planning has seen major advancements that stem from the availability of large reaction databases and artificial intelligence methodologies. SynRoute is a new retrosynthetic planning software tool that uses a relatively small number of general reaction templates, currently 263, along with a literature-based reaction database to find short, practical synthetic routes for target compounds. For each reaction template, a machine learning classifier is trained using data from the Pistachio reaction database to predict whether new computer-generated reactions based on the template are likely to work experimentally in the laboratory. This reaction generation methodology is used together with a vectorized Dijkstra-like search of top-scoring routes organized by synthetic strategies for easy browsing by a synthetic chemist. SynRoute was able to find routes for an average of 83% of compounds based on selection of random subsets of drug-like compounds from the ChEMBL database. Laboratory evaluation of 12 routes produced by SynRoute, to synthesize compounds not from the previous random subsets, demonstrated the ability to produce feasible overall synthetic strategies for all compounds evaluated.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Depiction of the overall algorithm to find diversified optimal routes using computer-generated reactions combined with the fixed reaction database and building blocks database. 1) best-first retrosynthetic generation of new reactions. 2) creation of subnetwork of compounds and reactions that can connect to the target compound. 3) vectorized Dijkstra search on this subnetwork to identify the top (diversified) k lowest cost routes.
Figure 2
Figure 2
Graphical User Interface (GUI) of SynRoute for executing a route search. The compound to synthesize can be drawn using the embedded JSME editor or by entering directly its SMILES representation.
Figure 3
Figure 3
SynRoute’s top-scoring strategy for the preparation of itraconazole.
Figure 4
Figure 4
Itraconazole scheme was performed on the AutoSyn platform. For reactions that were modified for adaption to the AutoSyn flow chemistry platform, the source of the reference conditions is given along with a rationale for why they were modified.
Figure 5
Figure 5
SynRoute’s top-scoring strategy for the preparation of bortezomib.
Figure 6
Figure 6
Bortezomib scheme on the AutoSyn platform.
See this image and copyright information in PMC

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