STOUT V2.0: SMILES to IUPAC name conversion using transformer models

Naming chemical compounds systematically is a complex task governed by a set of rules established by the International Union of Pure and Applied Chemistry (IUPAC). These rules are universal and widely accepted by chemists worldwide, but their complexity makes it challenging for individuals to consistently apply them accurately. A translation method can be employed to address this challenge. Accurate translation of chemical compounds from SMILES notation into their corresponding IUPAC names is crucial, as it can significantly streamline the laborious process of naming chemical structures. Here, we present STOUT (SMILES-TO-IUPAC-name translator) V2, which addresses this challenge by introducing a transformer-based model that translates string representations of chemical structures into IUPAC names. Trained on a dataset of nearly 1 billion SMILES strings and their corresponding IUPAC names, STOUT V2 demonstrates exceptional accuracy in generating IUPAC names, even for complex chemical structures. The model's ability to capture intricate patterns and relationships within chemical structures enables it to generate precise and standardised IUPAC names. While established deterministic algorithms remain the gold standard for systematic chemical naming, our work, enabled by access to OpenEye's Lexichem software through an academic license, demonstrates the potential of neural approaches to complement existing tools in chemical nomenclature.Scientific contribution STOUT V2, built upon transformer-based models, is a significant advancement from our previous work. The web application enhances its accessibility and utility. By making the model and source code fully open and well-documented, we aim to promote unrestricted use and encourage further development.

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Publication Details

Journal
Journal of Cheminformatics
Published
2024-12-27
DOI
https://doi.org/10.1186/s13321-024-00941-x
Citations
7
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
2.53

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article

STOUT V2.0: SMILES to IUPAC name conversion using transformer models

Kohulan Rajan, Christoph Steinbeck, Achim Zielesny
7 citations
Journal of Cheminformatics
Computational Drug Discovery Methods
2.53
article

STOUT V2.0: SMILES to IUPAC name conversion using transformer models

Kohulan Rajan, Christoph Steinbeck, Achim Zielesny
article en
7 citations

Abstract

Naming chemical compounds systematically is a complex task governed by a set of rules established by the International Union of Pure and Applied Chemistry (IUPAC). These rules are universal and widely accepted by chemists worldwide, but their complexity makes it challenging for individuals to consistently apply them accurately. A translation method can be employed to address this challenge. Accurate translation of chemical compounds from SMILES notation into their corresponding IUPAC names is crucial, as it can significantly streamline the laborious process of naming chemical structures. Here, we present STOUT (SMILES-TO-IUPAC-name translator) V2, which addresses this challenge by introducing a transformer-based model that translates string representations of chemical structures into IUPAC names. Trained on a dataset of nearly 1 billion SMILES strings and their corresponding IUPAC names, STOUT V2 demonstrates exceptional accuracy in generating IUPAC names, even for complex chemical structures. The model's ability to capture intricate patterns and relationships within chemical structures enables it to generate precise and standardised IUPAC names. While established deterministic algorithms remain the gold standard for systematic chemical naming, our work, enabled by access to OpenEye's Lexichem software through an academic license, demonstrates the potential of neural approaches to complement existing tools in chemical nomenclature.Scientific contribution STOUT V2, built upon transformer-based models, is a significant advancement from our previous work. The web application enhances its accessibility and utility. By making the model and source code fully open and well-documented, we aim to promote unrestricted use and encourage further development.

Journal of CheminformaticsVol. 16(1)
Friedrich Schiller University Jena (DE)
Friedrich-Schiller-Universität Jena, Deutsche Forschungsgemeinschaft
Decent work and economic growth
Openalex Percentile: Top 9%
Computational Drug Discovery Methods
2.53
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