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Influence of Template Size, Canonicalization, and Exclusivity for Retrosynthesis and Reaction Prediction Applications
Name
acs.jcim.1c01192.pdf
Description
Published version
Size
4.23 MB
Format
Adobe PDF
Checksum (MD5)
e01ef7fe09d6142ef666484eb7a00699
Author(s)
Heid, Esther
Liu, Jiannan
Aude, Andrea
Green, William H
Date Issued
December 23, 2021
Journal
Journal of Chemical Information and Modeling
Publisher
American Chemical Society (ACS)
Citation
Heid, Esther, Liu, Jiannan, Aude, Andrea and Green, William H. 2021. "Influence of Template Size, Canonicalization, and Exclusivity for Retrosynthesis and Reaction Prediction Applications." Journal of Chemical Information and Modeling.
Version
Final published version
Abstract
Heuristic and machine learning models for rank-ordering reaction templates comprise an important basis for computer-aided organic synthesis regarding both product prediction and retrosynthetic pathway planning. Their viability relies heavily on the quality and characteristics of the underlying template database. With the advent of automated reaction and template extraction software and consequently the creation of template databases too large for manual curation, a data-driven approach to assess and improve the quality of template sets is needed. We therefore systematically studied the influence of template generality, canonicalization, and exclusivity on the performance of different template ranking models. We find that duplicate and nonexclusive templates, i.e., templates which describe the same chemical transformation on identical or overlapping sets of molecules, decrease both the accuracy of the ranking algorithm and the applicability of the respective top-ranked templates significantly. To remedy the negative effects of nonexclusivity, we developed a general and computationally efficient framework to deduplicate and hierarchically correct templates. As a result, performance improved considerably for both heuristic and machine learning template ranking models, as well as multistep retrosynthetic planning models. The canonicalization and correction code is made freely available.
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
10.1021/acs.jcim.1c01192
