Chemical Name to Structure: OPSIN, an Open Source Solution

By Daniel M. Lowe, Peter T. Corbett, Peter Murray-Rust, Robert C. Glen. 2011

229 citations recorded by the source corpus.

Subfields: Molecular Biology, Physical and Theoretical Chemistry, Spectroscopy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. David S. Wishart
2. T. Ferrin
3. Thomas D. Goddard
4. Elaine C. Meng
5. Eric F. Pettersen
6. Gregory S. Couch
7. R. Greiner
8. Craig Knox

In Physical and Theoretical Chemistry

1. Philippe Schwaller
2. Hirotomo Moriwaki
3. Evan E. Bolton
4. Christoph Steinbeck
5. Oliver Schilter
6. Andrew D. White
7. Sam Cox
8. Andrés M Bran

In Spectroscopy

1. R. Greiner
2. Philippe Schwaller
3. Evan E. Bolton
4. Christoph Steinbeck
5. Oliver Schilter
6. David S. Wishart
7. Andrew D. White
8. Sam Cox

Citations in the corpus

• Mordred: a molecular descriptor calculator (2018, background): “It is a Python wrapper of numerous other libraries (e.g., Open Babel [16], RDKit [17], Chemistry Development Kit (CDK) [18], Indigo [19], JChem [20], and OPSIN [21]).”
• tmChem: a high performance approach for chemical named entity recognition and normalization (2015, unknown): ““benzene,” “pyridine” and “toluene”) and simple multipliers ("di,” “tri” and “tetra”), as derived from [28].”
• Augmenting large language models with chemistry tools (2023, methodology): “Our implementation queries chem-space 84 as a primary source, and upon failure queries PubChem 85 and the IUPAC to SMILES converter OPSIN 86 as a last option.”
• UCSF ChimeraX: Tools for structure building and analysis (2023, methodology): “Small-molecule structures can be fetched using web resources such as PubChem3D (Bolton et al., 2011), the PDB Chemical Components Dictionary (Westbrook et al., 2015), and translators for IUPAC names (Lowe et al., 2011) and SMILES strings (Oellien, n.d.).”
• STOUT: SMILES to IUPAC names using neural machine translation (2020, methodology): “For the predictions of IUPAC names as an output, the IUPAC names were re-converted to SMILES using OPSIN 2.5 [23] and canoni-calised using the CDK, with the resulting SMILES being utilized for Tanimoto similarity calculations.”
• ClassyFire: automated chemical classification with a comprehensive, computable taxonomy (2016, methodology): “In contrast, each IUPAC name is converted to the corresponding structure using the OPSIN library [39], before any chemical object is created and subsequently preprocessed.”