scbirlab/rasmussen-2025-csd

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@article{10.1186/s13321-025-01008-1, 
year = {2025}, 
title = {{SMILES all around: structure to SMILES conversion for transition metal complexes}}, 
author = {Rasmussen, Maria H. and Strandgaard, Magnus and Seumer, Julius and Hemmingsen, Laura K. and Frei, Angelo and Balcells, David and Jensen, Jan H.}, 
journal = {Journal of Cheminformatics}, 
issn = {0028-0836}, 
doi = {10.1186/s13321-025-01008-1}, 
pmid = {40296090}, 
pmcid = {PMC12039060}, 
url = {https://www.ncbi.nlm.nih.gov/pubmed/40296090}, 
abstract = {{We present a method for creating RDKit-parsable SMILES for transition metal complexes (TMCs) based on xyz-coordinates and overall charge of the complex. This can be viewed as an extension to the program xyz2mol that does the same for organic molecules. The only dependency is RDKit, which makes it widely applicable. One thing that has been lacking when it comes to generating SMILES from structure for TMCs is an existing SMILES dataset to compare with. Therefore, sanity-checking a method has required manual work. Therefore, we also generate SMILES two other ways; one where ligand charges and TMC connectivity are based on natural bond orbital (NBO) analysis from density functional theory (DFT) calculations utilizing recent work by Kneiding et al. (Digit Discov 2: 618-633, 2023). Another one fixes SMILES available through the Cambridge Structural Database (CSD), making them parsable by RDKit. We compare these three different ways of obtaining SMILES for a subset of the CSD

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dataset_licence({ "id": "scbirlab/rasmussen-2025-csd" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0