Reaction Data Curation I: Chemical Structures and Transformations Standardization

Timur R Gimadiev; Arkadii Lin; Valentina A Afonina; Dinar Batyrshin; Ramil I Nugmanov; Tagir Akhmetshin; Pavel Sidorov; Natalia Duybankova; Jonas Verhoeven; Joerg Wegner; Hugo Ceulemans; Andrey Gedich; Timur I Madzhidov; Alexandre Varnek

doi:10.1002/minf.202100119

Reaction Data Curation I: Chemical Structures and Transformations Standardization

Mol Inform. 2021 Dec;40(12):e2100119. doi: 10.1002/minf.202100119. Epub 2021 Aug 24.

Authors

Affiliations

¹ Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Kita 21 Nishi 10, Kita-ku, 001-0021, Sapporo, Japan.
² Laboratory of Chemoinformatics, UMR 7140 CNRS, University of Strasbourg, 4, Blaise Pascal str., 67081, Strasbourg, France.
³ Laboratory of Chemoinformatics and Molecular Modeling, Butlerov Institute of Chemistry, Kazan Federal University, 18, Kremlyovskaya str., 420008, Kazan, Russia.
⁴ Janssen Pharmaceutica, 30, Turnhoutseweg str., 2340, Beerse, Belgium.
⁵ Arcadia Inc., Bol'shoy Sampsoniyevskiy Prospekt, 28 κopпyc 2, 194044, St Petersburg, Russia.

PMID: 34427989
DOI: 10.1002/minf.202100119

Abstract

The quality of experimental data for chemical reactions is a critical consideration for any reaction-driven study. However, the curation of reaction data has not been extensively discussed in the literature so far. Here, we suggest a 4 steps protocol that includes the curation of individual structures (reactants and products), chemical transformations, reaction conditions and endpoints. Its implementation in Python3 using CGRTools toolkit has been used to clean three popular reaction databases Reaxys, USPTO and Pistachio. The curated USPTO database is available in the GitHub repository (Laboratoire-de-Chemoinformatique/Reaction_Data_Cleaning).

Keywords: Pistachio; Reaxys; USPTO; big data; chemical reactions; data cleaning.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Data Curation*
Databases, Factual
Reference Standards