Computer-Assisted Retrosynthesis Based on Molecular Similarity
Author(s) -
Connor W. Coley,
Luke Rogers,
William H. Green,
Klavs F. Jensen
Publication year - 2017
Publication title -
acs central science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.893
H-Index - 76
eISSN - 2374-7951
pISSN - 2374-7943
DOI - 10.1021/acscentsci.7b00355
Subject(s) - retrosynthetic analysis , ranking (information retrieval) , similarity (geometry) , analogy , metric (unit) , computer science , extension (predicate logic) , encode , artificial intelligence , data mining , machine learning , information retrieval , chemistry , engineering , programming language , stereochemistry , linguistics , total synthesis , philosophy , operations management , biochemistry , image (mathematics) , gene
We demonstrate molecular similarity to be a surprisingly effective metric for proposing and ranking one-step retrosynthetic disconnections based on analogy to precedent reactions. The developed approach mimics the retrosynthetic strategy defined implicitly by a corpus of known reactions without the need to encode any chemical knowledge. Using 40 000 reactions from the patent literature as a knowledge base, the recorded reactants are among the top 10 proposed precursors in 74.1% of 5000 test reactions, providing strong quantitative support for our methodology. Extension of the one-step strategy to multistep pathway planning is demonstrated and discussed for two exemplary drug products.
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