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Andronov, M.* ; Voinarovska, V. ; Andronova, N.* ; Wand, M.* ; Clevert, D.A.* ; Schmidhuber, J.*

Reagent prediction with a molecular transformer improves reaction data quality.

Chem. Sci. 14, 3235-3246 (2023)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Automated synthesis planning is key for efficient generative chemistry. Since reactions of given reactants may yield different products depending on conditions such as the chemical context imposed by specific reagents, computer-aided synthesis planning should benefit from recommendations of reaction conditions. Traditional synthesis planning software, however, typically proposes reactions without specifying such conditions, relying on human organic chemists who know the conditions to carry out suggested reactions. In particular, reagent prediction for arbitrary reactions, a crucial aspect of condition recommendation, has been largely overlooked in cheminformatics until recently. Here we employ the Molecular Transformer, a state-of-the-art model for reaction prediction and single-step retrosynthesis, to tackle this problem. We train the model on the US patents dataset (USPTO) and test it on Reaxys to demonstrate its out-of-distribution generalization capabilities. Our reagent prediction model also improves the quality of product prediction: the Molecular Transformer is able to substitute the reagents in the noisy USPTO data with reagents that enable product prediction models to outperform those trained on plain USPTO. This makes it possible to improve upon the state-of-the-art in reaction product prediction on the USPTO MIT benchmark.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Organic-chemistry; Classification; Computer; Model; Methodology; System
ISSN (print) / ISBN 2041-6520
e-ISSN 2041-6539
Zeitschrift Chemical Science
Quellenangaben Band: 14, Heft: 12, Seiten: 3235-3246 Artikelnummer: , Supplement: ,
Verlag Royal Society of Chemistry (RSC)
Verlagsort Thomas Graham House, Science Park, Milton Rd, Cambridge Cb4 0wf, Cambs, England
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Structural Biology (STB)
Förderungen Marie Curie Actions (MSCA)
European Union