RENATE: A Pseudo-retrosynthetic Tool for Synthetically Accessible de novo Design

Gian Marco Ghiandoni, Michael J. Bodkin, Beining Chen, Dimitar Hristozov, James E. A. Wallace, James Webster, Valerie J. Gillet (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
32 Downloads (Pure)

Abstract

Reaction-based de novo design refers to the generation of synthetically accessible molecules using transformation rules extracted from known reactions in the literature. In this context, we have previously described the extraction of reaction vectors from a reactions database and their coupling with a structure generation algorithm for the generation of novel molecules from a starting material. An issue when designing molecules from a starting material is the combinatorial explosion of possible product molecules that can be generated, especially for multistep syntheses. Here, we present the development of RENATE, a reaction-based de novo design tool, which is based on a pseudo-retrosynthetic fragmentation of a reference ligand and an inside-out approach to de novo design. The reference ligand is fragmented; each fragment is used to search for similar fragments as building blocks; the building blocks are combined into products using reaction vectors; and a synthetic route is suggested for each product molecule. The RENATE methodology is presented followed by a retrospective validation to recreate a set of approved drugs. Results show that RENATE can generate very similar or even identical structures to the corresponding input drugs, hence validating the fragmentation, search, and design heuristics implemented in the tool.

Original languageEnglish
Article number2100207
Number of pages8
JournalMolecular Informatics
Volume41
Issue number4
Early online date8 Nov 2021
DOIs
Publication statusPublished - Apr 2022

Keywords

  • de novo drug design
  • patents
  • pharmaceuticals
  • reaction informatics

ASJC Scopus subject areas

  • Structural Biology
  • Molecular Medicine
  • Drug Discovery
  • Computer Science Applications
  • Organic Chemistry

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