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CGRdb2.0: A Python Database Management System for Molecules, Reactions, and Chemical Data
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    CGRdb2.0: A Python Database Management System for Molecules, Reactions, and Chemical Data
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    • Timur Gimadiev
      Timur Gimadiev
      Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Kita 21 Nishi 10, Kita-ku, 001-0021 Sapporo, Japan
    • Ramil Nugmanov
      Ramil Nugmanov
      Laboratory of Chemoinformatics and Molecular Modeling, Butlerov Institute of Chemistry, Kazan Federal University, 18, Kremlyovskaya str., 420008 Kazan, Russia
    • Aigul Khakimova
      Aigul Khakimova
      JSC ≪BIOCAD≫, Petrodvortsoviy District, Strelna, Svyazi st., Bld. 34, Liter A, 198515 St. Petersburg, Russia
    • Adeliya Fatykhova
      Adeliya Fatykhova
      Laboratory of Chemoinformatics and Molecular Modeling, Butlerov Institute of Chemistry, Kazan Federal University, 18, Kremlyovskaya str., 420008 Kazan, Russia
    • Timur Madzhidov*
      Timur Madzhidov
      Laboratory of Chemoinformatics and Molecular Modeling, Butlerov Institute of Chemistry, Kazan Federal University, 18, Kremlyovskaya str., 420008 Kazan, Russia
      *Email: [email protected]
    • Pavel Sidorov*
      Pavel Sidorov
      Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Kita 21 Nishi 10, Kita-ku, 001-0021 Sapporo, Japan
      *Email: [email protected]
    • Alexandre Varnek*
      Alexandre Varnek
      Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Kita 21 Nishi 10, Kita-ku, 001-0021 Sapporo, Japan
      Laboratory of Chemoinformatics, UMR 7140 CNRS, University of Strasbourg, 4, Blaise Pascal Str., 67081 Strasbourg, France
      *Email: [email protected]
    Other Access OptionsSupporting Information (2)

    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2022, 62, 9, 2015–2020
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    https://doi.org/10.1021/acs.jcim.1c01105
    Published November 29, 2021
    Copyright © 2021 American Chemical Society

    Abstract

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    This work introduces CGRdb2.0─an open-source database management system for molecules, reactions, and chemical data. CGRdb2.0 is a Python package connecting to a PostgreSQL database that enables native searches for molecules and reactions without complicated SQL syntax. The library provides out-of-the-box implementations for similarity and substructure searches for molecules, as well as similarity and substructure searches for reactions in two ways─based on reaction components and based on the Condensed Graph of Reaction approach, the latter significantly accelerating the performance. In benchmarking studies with the RDKit database cartridge, we demonstrate that CGRdb2.0 performs searches faster for smaller data sets, while allowing for interactive access to the retrieved data.

    Copyright © 2021 American Chemical Society

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    Supporting Information

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.1c01105.

    • Structures of reactions and corresponding CGRs used in the reaction benchmark study (PDF)

    • Results of benchmarking studies on compounds and reaction, using both RDKit-db and CGRdb2.0 (XLSX)

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    Cited By

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    This article is cited by 8 publications.

    1. Mohammad Ali, Yuta Mizuno, Seiji Akiyama, Yuuya Nagata, Tamiki Komatsuzaki. Enumeration Approach to Atom-to-Atom Mapping Accelerated by Ising Computing. Journal of Chemical Information and Modeling 2025, Article ASAP.
    2. Ramil Nugmanov. PaCh (Packed Chemicals): Computationally Effective Binary Format for Chemical Structure Encoding. Journal of Chemical Information and Modeling 2024, 64 (8) , 3173-3179. https://doi.org/10.1021/acs.jcim.3c01720
    3. Ramil Nugmanov, Natalia Dyubankova, Andrey Gedich, Joerg Kurt Wegner. Bidirectional Graphormer for Reactivity Understanding: Neural Network Trained to Reaction Atom-to-Atom Mapping Task. Journal of Chemical Information and Modeling 2022, 62 (14) , 3307-3315. https://doi.org/10.1021/acs.jcim.2c00344
    4. Matthias Rarey, Marc C. Nicklaus, Wendy Warr. Special Issue on Reaction Informatics and Chemical Space. Journal of Chemical Information and Modeling 2022, 62 (9) , 2009-2010. https://doi.org/10.1021/acs.jcim.2c00390
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    6. Fedor V. Ryzhkov, Yuliya E. Ryzhkova, Michail N. Elinson. Python tools for structural tasks in chemistry. Molecular Diversity 2024, 11 https://doi.org/10.1007/s11030-024-10889-7
    7. Pavel Sidorov, Nobuya Tsuji. A Primer on 2D Descriptors in Selectivity Modeling for Asymmetric Catalysis. Chemistry – A European Journal 2024, 30 (10) https://doi.org/10.1002/chem.202302837
    8. Lung-Yi Chen, Yi-Pei Li. Machine learning-guided strategies for reaction conditions design and optimization. Beilstein Journal of Organic Chemistry 2024, 20 , 2476-2492. https://doi.org/10.3762/bjoc.20.212

    Journal of Chemical Information and Modeling

    Cite this: J. Chem. Inf. Model. 2022, 62, 9, 2015–2020
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jcim.1c01105
    Published November 29, 2021
    Copyright © 2021 American Chemical Society

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