ArticleChemical science2019
Computational design of syntheses leading to compound libraries or isotopically labelled targets.
Article in Chemical science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Enhancing Monte Carlo Tree Search for Retrosynthesis.Journal of chemical information and modeling · 2025Article
- SynTemp: Efficient Extraction of Graph-Based Reaction Rules from Large-Scale Reaction Databases.Journal of chemical information and modeling · 2025Article
- Improving route development using convergent retrosynthesis planning.Journal of cheminformatics · 2025Article
- Machine learning-guided strategies for reaction conditions design and optimization.Beilstein journal of organic chemistry · 2024Review
- Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery.Chemical science · 2023Review
- Designing a multilayer film via machine learning of scientific literature.Scientific reports · 2022Article
- Deep learning and generative methods in cheminformatics and chemical biology: navigating small molecule space intelligently.The Biochemical journal · 2020Review
- Article
- Towards efficient discovery of green synthetic pathways with Monte Carlo tree search and reinforcement learning.Chemical science · 2020Article
- Computer-generated "synthetic contingency" plans at times of logistics and supply problems: scenarios for hydroxychloroquine and remdesivir.Chemical science · 2020Article
- Automatic retrosynthetic route planning using template-free models.Chemical science · 2020Article
- Minimal manual input.Nature chemistry · 2020Article
- Computational design of syntheses leading to compound libraries or isotopically labelled targets.Chemical science · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although computer programs for retrosynthetic planning have shown improved and in some cases quite satisfactory performance in designing routes leading to specific, individual targets, no algorithms capable of planning syntheses of entire target libraries - important in modern drug discovery - have yet been reported. This study describes how network-search routines underlying existing retrosynthetic programs can be adapted and extended to multi-target design operating on one common search graph, benefitting from the use of common intermediates and reducing the overall synthetic cost. Implementation in the Chematica platform illustrates the usefulness of such algorithms in the syntheses of either (i) all members of a user-defined library, or (ii) the most synthetically accessible members of this library. In the latter case, algorithms are also readily adapted to the identification of the most facile syntheses of isotopically labelled targets. These examples are industrially relevant in the context of hit-to-lead optimization and syntheses of isotopomers of various bioactive molecules.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.