--- license: mit task_categories: - text-classification - text2text-generation - translation - zero-shot-classification tags: - chemistry - biology - SMILES - benchmark size_categories: - 1k > To benefit the broader computational chemistry community and improve the > quality and diversity of public-domain ADME data sets we have disclosed a > collection of 3521 diverse compounds selected from commercially available > compound libraries (i.e. Enamine, eMolecules, WuXi LabNetwork, Mcule) and > tested them against our internal six ADME in vitro assays described in this > study using the same experimental conditions as of our in-house datasets. > ### Dataset Description - **Curated by:** Biogen - **License:** MIT ### Dataset Sources - **Repository:** https://github.com/molecularinformatics/Computational-ADME - **Paper:** https://doi.org/10.1021/acs.jcim.3c00160 ## Uses Benchmarking chemical property prediction models. ## Dataset Structure The train-test splits are generated by scaffold. The column headings of the data are: - **SMILES**: Original SMILES string, as in the original data release in the [GitHub repositiory](https://github.com/molecularinformatics/Computational-ADME) - **smiles**: Canonicalized SMILES string - **id**: Numeric structure identifier - **inchikey**: Unique structure identifier - **scaffold**: Murcko scaffold - **mwt**: Molecular weight - **clogp**: Crippen LogP - **tpsa**: Calculated topological polar surface area. The following columns are ADME properties: - log_hlm: human liver microsomal (HLM) stability (Clint, mL/min/kg) - log_mdr1_mdck_er: MDR1-MDCK efflux ratio - log_solubility: solubility at pH 6.8 (ug/mL) - log_plasma_protein_binding_human: human plasma protein binding (hPPB) percent unbound - log_plasma_protein_binding_rat: rat plasma protein binding (rPPB) percent unbound - log_rlm: rat liver microsomal (RLM) stability (Clint, mL/min/kg) ## Dataset Creation ### Curation Rationale To make the Biogen ADME dataset readily available with light preprocessing. #### Data Collection and Processing Additional properties and scaffold splits were calculated using [schemist](https://github.com/scbirlab/schemist), a tool for processing chemical datasets. #### Who are the source data producers? Biogen #### Personal and Sensitive Information None ## Citation **BibTeX:** ``` @article{doi:10.1021/acs.jcim.3c00160, author = {Fang, Cheng and Wang, Ye and Grater, Richard and Kapadnis, Sudarshan and Black, Cheryl and Trapa, Patrick and Sciabola, Simone}, title = {Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective}, journal = {Journal of Chemical Information and Modeling}, volume = {63}, number = {11}, pages = {3263-3274}, year = {2023}, doi = {10.1021/acs.jcim.3c00160}, note = {PMID: 37216672}, URL = {https://doi.org/10.1021/acs.jcim.3c00160}, eprint = {https://doi.org/10.1021/acs.jcim.3c00160} } ``` ## Dataset Card Contact [@eachanjohnson](https://huggingface.co/eachanjohnson)