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Towards a Universal SMILES representation - A standard method to generate canonical SMILES based on the InChI
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AbstractBackgroundThere are two line notations of chemical structures that have established themselves in the field: the SMILES string and the InChI string. The InChI aims to provide a unique, or canonical, identifier for chemical structures, while SMILES strings are widely used for storage and interchange of chemical structures, but no standard exists to generate a canonical SMILES string.ResultsI describe how to use the InChI canonicalisation to derive a canonical SMILES string in a straightforward way, either incorporating the InChI normalisations (Inchified SMILES) or not (Universal SMILES). This is the first description of a method to generate canonical SMILES that takes stereochemistry into account. When tested on the 1.1 m compounds in the ChEMBL database, and a 1 m compound subset of the PubChem Substance database, no canonicalisation failures were found with Inchified SMILES. Using Universal SMILES, 99.79% of the ChEMBL database was canonicalised successfully and 99.77% of the PubChem subset.ConclusionsThe InChI canonicalisation algorithm can successfully be used as the basis for a common standard for canonical SMILES. While challenges remain – such as the development of a standard aromatic model for SMILES – the ability to create the same SMILES using different toolkits will mean that for the first time it will be possible to easily compare the chemical models used by different toolkits.
Title: Towards a Universal SMILES representation - A standard method to generate canonical SMILES based on the InChI
Description:
AbstractBackgroundThere are two line notations of chemical structures that have established themselves in the field: the SMILES string and the InChI string.
The InChI aims to provide a unique, or canonical, identifier for chemical structures, while SMILES strings are widely used for storage and interchange of chemical structures, but no standard exists to generate a canonical SMILES string.
ResultsI describe how to use the InChI canonicalisation to derive a canonical SMILES string in a straightforward way, either incorporating the InChI normalisations (Inchified SMILES) or not (Universal SMILES).
This is the first description of a method to generate canonical SMILES that takes stereochemistry into account.
When tested on the 1.
1 m compounds in the ChEMBL database, and a 1 m compound subset of the PubChem Substance database, no canonicalisation failures were found with Inchified SMILES.
Using Universal SMILES, 99.
79% of the ChEMBL database was canonicalised successfully and 99.
77% of the PubChem subset.
ConclusionsThe InChI canonicalisation algorithm can successfully be used as the basis for a common standard for canonical SMILES.
While challenges remain – such as the development of a standard aromatic model for SMILES – the ability to create the same SMILES using different toolkits will mean that for the first time it will be possible to easily compare the chemical models used by different toolkits.
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