OMG: Open Molecule Generator.
Abstract
Computer Assisted Structure Elucidation has been used for decades to discover the chemical structure of unknown compounds. In this work we introduce the first open source structure generator, Open Molecule Generator (OMG), which for a given elemental composition produces all non-isomorphic chemical structures that match that elemental composition. Furthermore, this structure generator can accept as additional input one or multiple non-overlapping prescribed substructures to drastically reduce the number of possible chemical structures. Being open source allows for customization and future extension of its functionality. OMG relies on a modified version of the Canonical Augmentation Path, which grows intermediate chemical structures by adding bonds and checks that at each step only unique molecules are produced. In order to benchmark the tool, we generated chemical structures for the elemental formulas and substructures of different metabolites and compared the results with a commercially available structure generator. The results obtained, i.e. the number of molecules generated, were identical for elemental compositions having only C, O and H. For elemental compositions containing C, O, H, N, P and S, OMG produces all the chemically valid molecules while the other generator produces more, yet chemically impossible, molecules. The chemical completeness of the OMG results comes at the expense of being slower than the commercial generator. In addition to being open source, OMG clearly showed the added value of constraining the solution space by using multiple prescribed substructures as input. We expect this structure generator to be useful in many fields, but to be especially of great importance for metabolomics, where identifying unknown metabolites is still a major bottleneck.
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BibTeX
@article{peironcely2026open,
title = {{OMG: Open Molecule Generator.}},
author = {Julio E Peironcely and Miguel Rojas-Chertó and Davide Fichera and Theo Reijmers and Leon Coulier and Jean-Loup Faulon and Thomas Hankemeier},
journal = {Journal of Cheminformatics},
year = {2026},
month = oct,
doi = {10.1186/1758-2946-4-21},
url = {https://hal.science/hal-05779647v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - OMG: Open Molecule Generator.
AU - Julio E Peironcely
AU - Miguel Rojas-Chertó
AU - Davide Fichera
AU - Theo Reijmers
AU - Leon Coulier
AU - Jean-Loup Faulon
AU - Thomas Hankemeier
PY - 2026
DA - 2026/10/05
JO - Journal of Cheminformatics
DO - 10.1186/1758-2946-4-21
UR - https://hal.science/hal-05779647v1
AB - Computer Assisted Structure Elucidation has been used for decades to discover the chemical structure of unknown compounds. In this work we introduce the first open source structure generator, Open Molecule Generator (OMG), which for a given elemental composition produces all non-isomorphic chemical structures that match that elemental composition. Furthermore, this structure generator can accept as additional input one or multiple non-overlapping prescribed substructures to drastically reduce the number of possible chemical structures. Being open source allows for customization and future extension of its functionality. OMG relies on a modified version of the Canonical Augmentation Path, which grows intermediate chemical structures by adding bonds and checks that at each step only unique molecules are produced. In order to benchmark the tool, we generated chemical structures for the elemental formulas and substructures of different metabolites and compared the results with a commercially available structure generator. The results obtained, i.e. the number of molecules generated, were identical for elemental compositions having only C, O and H. For elemental compositions containing C, O, H, N, P and S, OMG produces all the chemically valid molecules while the other generator produces more, yet chemically impossible, molecules. The chemical completeness of the OMG results comes at the expense of being slower than the commercial generator. In addition to being open source, OMG clearly showed the added value of constraining the solution space by using multiple prescribed substructures as input. We expect this structure generator to be useful in many fields, but to be especially of great importance for metabolomics, where identifying unknown metabolites is still a major bottleneck.
SN - 1758-2946
SN - 1758-2946
ER -