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AAM_benchmarking_preprint_27.09.2020.pdf (612.61 kB)

Atom-to-Atom Mapping: A Benchmarking Study of Popular Mapping Algorithms and Consensus Strategies

preprint
submitted on 27.09.2020 and posted on 30.09.2020 by Timur Madzhidov, Arkadii I. Lin, Ramil Nugmanov, Natalia Dyubankova, Timur Gimadiev, Jörg Kurt Wegner, Assima Rakhimbekova, Tagir Akhmetshin, Zarina Ibragimova, Alexandre Varnek, Rail Suleymanov, Hugo Ceulemans, Jonas Verhoeven
Here, we discuss a reaction standardization protocol followed by a comparison of popular Atom-to-atom mapping (AAM) tools (ChemAxon, Indigo, RDTool, NextMove and RXNMapper) as well as some consensus AAM strategies. For this purpose, a dataset of 1851 manually curated and mapped reactions was prepared (the Golden dataset) and used as a reference set. It has been found that RXNMapper possesses the highest accuracy, despite the fact that it has some clear disadvantages. Finally, RXNMapper was selected as the best tool, and it was applied to map the USPTO dataset. The standardization protocol used to prepare the data, as well as the data itself are available in the GitHub repository https://github.com/Laboratoire-de-Chemoinformatique.



History

Email Address of Submitting Author

varnek@unistra.fr

Institution

University of Strasbourg

Country

France

ORCID For Submitting Author

0000-0003-1886-925X

Declaration of Conflict of Interest

there is no conflict of interest

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