ArticleMolecular informatics2022
RENATE: A Pseudo-retrosynthetic Tool for Synthetically Accessible de novo Design.
Article in Molecular informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Article
- Generative Deep Learning for de Novo Drug Design─A Chemical Space Odyssey.Journal of chemical information and modeling · 2025Review
- Synthetically accessible de novo design using reaction vectors: Application to PARP1 inhibitors.Molecular informatics · 2024Article
- A molecule perturbation software library and its application to study the effects of molecular design constraints.Journal of cheminformatics · 2023Article
- MegaSyn: Integrating Generative Molecular Design, Automated Analog Designer, and Synthetic Viability Prediction.ACS omega · 2022Article
- RENATE: A Pseudo-retrosynthetic Tool for Synthetically Accessible de novo Design.Molecular informatics · 2022Article
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Authors and funding
7 authors.
Funding
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.
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