Autofluorescent compounds identified in HTS compound libraries (Simeonov et al, 2008)
This dataset includes the CID, SMILES, InChi representation and InChi key, as well as the AID for the active compounts identified in Simeonove et al.
Quickstart Usage
From within python load the datasets library to access the dataset and pandas for parsing:
>>> import datasets
>>> import pandas as pd
ActiveCompounds = datasets.load_dataset("LuisTR40584/Simeonov2008")
acdf = ActiveCompounds["train"].to_pandas()
print(acdf.columns())
print(acdf.head())
Dataset Details
Dataset Description
The source data comes from a study testing for autoflorescence in compounds within common Hightrhoughput Screening libraries. Autoflorescence of compunds for HTS can interfere with the result of the screen, particularly if fluorescence is used as a readout. Here the authors tested over 70,000 compounds from different HTS libraries, in which they identified over 7,000 compounds with some kind of autoflorescence in different emission ranges. This dataset includes those active compounds, including the corresponding AID of their entry, their CID, SMILES, InChi, InChi key, as well as standarized SMILES (field labeled as "Smiles_Sanatized").
Dataset Sources
- Data was obtained from PubChem BioAssays associated to the paper below: Simeonov, A., Jadhav, A., Thomas, C. J., Wang, Y., Huang, R., Southall, N. T., Shinn, P., Smith, J., Austin, C. P., Auld, D. S., & Inglese, J. (2008). Fluorescence spectroscopic profiling of compound libraries. Journal of medicinal chemistry, 51(8), 2363–2371. https://doi.org/10.1021/jm701301m
- Downloads last month
- 3