RDCanon: A Python Package for Canonicalizing the Order of Tokens in SMARTS Queries
Name
RDCanon.pdf
Description
Submitted version
Size
1.26 MB
Format
Adobe PDF
Checksum (MD5)
af8d25e5910aa1923fdb253bf2669b34
Author(s)
Mahjour, Babak A
Coley, Connor W
Date Issued
March 15, 2024
Journal
Journal of Chemical Information and Modeling
Publisher
American Chemical Society
Citation
RDCanon: A Python Package for Canonicalizing the Order of Tokens in SMARTS Queries. Babak A. Mahjour and Connor W. Coley. Journal of Chemical Information and Modeling 2024 64 (8), 2948-2954.
Version
Author's final manuscript
Abstract
SMARTS is a widely used language in cheminformatics for defining substructural queries for database lookups, reaction templates for chemical transformations, and other applications. As an extension to SMILES, many SMARTS patterns can represent the same query. Despite this, no canonicalization algorithm invariant of the line notation sequence or atomic numbering is publicly available. Here, we introduce RDCanon, an open-source Python package that can be used to standardize SMARTS queries. RDCanon is designed to ensure that the sequence of atomic queries remains consistent for all graphs representing the same substructure query and to ensure a canonical sequence of primitives within each individual atom query; furthermore, the algorithm can be applied to canonicalize the order of reactants, agents, and products and their atom map numbers in reaction SMARTS templates. As part of its canonicalization algorithm, RDCanon provides a mechanism in which the canonicalized SMARTS is optimized for speed against specific molecular databases. Several case studies are provided to showcase improved efficiency in substructure matching and retrosynthetic analysis.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
10.1021/acs.jcim.4c00138
