Reaction Data Curation I: Chemical Structures and Transformations Standardization. Issue 12 (24th August 2021)

• Record Type: Journal Article
• Authors: Gimadiev, Timur R.; Lin, Arkadii; Afonina, Valentina A.; Batyrshin, Dinar; Nugmanov, Ramil I.; Akhmetshin, Tagir; Sidorov, Pavel; Duybankova, Natalia; Verhoeven, Jonas; Wegner, Joerg; Ceulemans, Hugo; Gedich, Andrey; Madzhidov, Timur I.; Varnek, Alexandre
• Is Part Of: Molecular informatics. Volume 40:Issue 12(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-08-24
• Subjects: chemical reactions -- data cleaning -- big data -- Reaxys -- USPTO -- Pistachio; Cheminformatics -- Periodicals; QSAR (Biochemistry) -- Periodicals; Structure-activity relationships (Biochemistry) -- Periodicals; Drugs -- Structure-activity relationships -- Periodicals; 615.19
• DOI: 10.1002/minf.202100119
• Languages: English
• ISSNs: 1868-1743

Abstract

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). Abstract :