One step retrosynthesis of drugs from commercially available chemical building blocks and conceivable coupling reactions

Abstract

In this report, the pharmaceuticals listed in DrugBank were structurally mapped to a commercial catalog of chemical feedstocks through reaction agnostic one step retrosynthetic decomposition. Enumerative combinatorics was utilized to retrosynthesize target molecules into commercially available building blocks, wherein only the bond formed and the minimal substructure template of each building block class are considered. In contrast to the status quo in automated retrosynthesis, our algorithm may suggest reactions that do not yet exist but, if they did, could enable the synthesis of drugs in just one reaction step from commercial feedstocks. Cross-referencing synthons to commercial datasets can thus reveal valuable reaction classes for development in addition to streamlining drug production. Decomposed synthons were linked to target molecules by transformations that form one bond after the elimination of each synthon's respective reactive functional handle, as indicated by their building block class. Specific reactivities were analyzed after post hoc refinement and clustering of commercial synthons. Maps between boronates, bromides, iodides, amines, acids, chlorides, alcohols, and various C–H motifs to form alkyl–alkyl, alkyl–aryl, and aryl–aryl carbon–carbon, carbon–nitrogen, and carbon–oxygen bonds are reported herein, with specific examples for each provided.

Graphical abstract: One step retrosynthesis of drugs from commercially available chemical building blocks and conceivable coupling reactions

Supplementary files

Article information

Article type
Paper
Submitted
14 Jul 2025
Accepted
17 Nov 2025
First published
16 Dec 2025
This article is Open Access
Creative Commons BY license

Digital Discovery, 2025, Advance Article

One step retrosynthesis of drugs from commercially available chemical building blocks and conceivable coupling reactions

B. Mahjour, F. Katzenburg, E. Lammi and T. Cernak, Digital Discovery, 2025, Advance Article , DOI: 10.1039/D5DD00310E

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