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SynRoute: A Retrosynthetic Planning Software.
Latendresse, Mario; Malerich, Jeremiah P; Herson, James; Krummenacker, Markus; Szeto, Judy; Vu, Vi-Anh; Collins, Nathan; Madrid, Peter B.
Afiliação
  • Latendresse M; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
  • Malerich JP; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
  • Herson J; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
  • Krummenacker M; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
  • Szeto J; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
  • Vu VA; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
  • Collins N; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
  • Madrid PB; SRI International, 333 Ravenswood Ave, Menlo Park, California 94025, United States.
J Chem Inf Model ; 63(17): 5484-5495, 2023 09 11.
Article em En | MEDLINE | ID: mdl-37635298
ABSTRACT
Computer-assisted synthetic planning has seen major advancements that stem from the availability of large reaction databases and artificial intelligence methodologies. SynRoute is a new retrosynthetic planning software tool that uses a relatively small number of general reaction templates, currently 263, along with a literature-based reaction database to find short, practical synthetic routes for target compounds. For each reaction template, a machine learning classifier is trained using data from the Pistachio reaction database to predict whether new computer-generated reactions based on the template are likely to work experimentally in the laboratory. This reaction generation methodology is used together with a vectorized Dijkstra-like search of top-scoring routes organized by synthetic strategies for easy browsing by a synthetic chemist. SynRoute was able to find routes for an average of 83% of compounds based on selection of random subsets of drug-like compounds from the ChEMBL database. Laboratory evaluation of 12 routes produced by SynRoute, to synthesize compounds not from the previous random subsets, demonstrated the ability to produce feasible overall synthetic strategies for all compounds evaluated.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software / Inteligência Artificial Tipo de estudo: Prognostic_studies Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software / Inteligência Artificial Tipo de estudo: Prognostic_studies Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos