ArticleChemical science2023
Multistep retrosynthesis combining a disconnection aware triple transformer loop with a route penalty score guided tree search.
Article in Chemical science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Enhancing biocatalytic retrosynthesis with a graph-to-graph model.Chemical science · 2026Article
- Assigning the stereochemistry of natural products by machine learning.Journal of cheminformatics · 2026Article
- Review
- Data augmentation in a triple transformer loop retrosynthesis model.Digital discovery · 2026Article
- A virtual platform for automated hybrid organic-enzymatic synthesis planning.Nature communications · 2025Article
- Data-driven recommendation of agents, temperature, and equivalence ratios for organic synthesis.Chemical science · 2025Article
- ASKCOS: Open-Source, Data-Driven Synthesis Planning.Accounts of chemical research · 2025Article
- Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry.Chemical Society reviews · 2025Review
- Investigations into the Efficiency of Computer-Aided Synthesis Planning.Journal of chemical information and modeling · 2025Article
- Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning.Beilstein journal of organic chemistry · 2025Review
- Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review.ACS synthetic biology · 2024Article
- DrugGym: A testbed for the economics of autonomous drug discovery.bioRxiv : the preprint server for biology · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computer-aided synthesis planning (CASP) aims to automatically learn organic reactivity from literature and perform retrosynthesis of unseen molecules. CASP systems must learn reactions sufficiently precisely to propose realistic disconnections, while avoiding overfitting to leave room for diverse options, and explore possible routes such as to allow short synthetic sequences to emerge. Herein we report an open-source CASP tool proposing original solutions to both challenges. First, we use a triple transformer loop (TTL) predicting starting materials (T1), reagents (T2), and products (T3) to explore various disconnection sites defined by combining systematic, template-based, and transformer-based tagging procedures. Second, we integrate TTL into a multistep tree search algorithm (TTLA) prioritizing sequences using a route penalty score (RPScore) considering the number of steps, their confidence score, and the simplicity of all intermediates along the route. Our approach favours short synthetic routes to commercial starting materials, as exemplified by retrosynthetic analyses of recently approved drugs.
Identifiers
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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.