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STOUT-Rajan-Zielesny-Steinbeck.pdf (1.53 MB)

STOUT: SMILES to IUPAC Names Using Neural Machine Translation

submitted on 21.12.2020, 12:26 and posted on 22.12.2020, 13:14 by Kohulan Rajan, Achim Zielesny, Christoph Steinbeck

Chemical compounds can be identified through a graphical depiction, a suitable string representation, or a chemical name. A universally accepted naming scheme for chemistry was established by the International Union of Pure and Applied Chemistry (IUPAC) based on a set of rules. Due to the complexity of this rule set a correct chemical name assignment remains challenging for human beings and there are only a few rule-based cheminformatics toolkits available that support this task in an automated manner.

Here we present STOUT (SMILES-TO-IUPAC-name translator), a deep-learning neural machine translation approach to generate the IUPAC name for a given molecule from its SMILES string as well as the reverse translation, i.e., predicting the SMILES string from the IUPAC name. The open system demonstrates a test accuracy of about 90% correct predictions, also incorrect predictions show a remarkable similarity between true and predicted compounds.


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Friedrich-Schiller-University Jena



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Declaration of Conflict of Interest

No Conflict of Interest