https://github.com/nanxstats/logd74
A high-quality hand-curated logD7.4 dataset of 1,130 compounds
https://github.com/nanxstats/logd74
cheminformatics chemometrics dataset drug-discovery qsar qspr
Last synced: 7 months ago
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A high-quality hand-curated logD7.4 dataset of 1,130 compounds
- Host: GitHub
- URL: https://github.com/nanxstats/logd74
- Owner: nanxstats
- Created: 2017-04-25T04:52:47.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-11-23T04:26:12.000Z (almost 8 years ago)
- Last Synced: 2025-03-05T22:11:51.820Z (7 months ago)
- Topics: cheminformatics, chemometrics, dataset, drug-discovery, qsar, qspr
- Homepage: https://nanx.me/papers/logd.pdf
- Size: 98.6 KB
- Stars: 20
- Watchers: 3
- Forks: 9
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# logD7.4 of 1,130 Compounds 
This repository archives a high-quality hand-curated [lipophilicity dataset](logd74.tsv) that includes the chemical structure (SMILES) of 1,130 organic compounds and their _n_-octanol/buffer solution distribution coefficients at pH 7.4 (logD7.4), originally curated by [our paper](http://onlinelibrary.wiley.com/doi/10.1002/cem.2718/full) ([PDF](https://nanx.me/papers/logd.pdf)).
## About logD7.4
As a determinant of several ADME properties, lipophilicity (logD7.4) is a key physical property in the development of small molecule oral drugs. This dataset can be applied for method benchmarking in regression modeling, cheminformatics, and chemometrics research.
## Paper Citation
If you find this dataset useful in your research, please cite our paper:
Formatted citation:
Wang, J-B., D-S. Cao, M-F. Zhu, Y-H. Yun, N. Xiao, Y-Z. Liang (2015). _In silico_ evaluation of logD7.4 and comparison with other prediction methods. _Journal of Chemometrics_, 29(7), 389-398.
BibTeX entry:
```
@article{logd2015,
title={\textit{In silico} evaluation of $\text{logD}_{7.4}$ and comparison with other prediction methods},
author={Wang, Jian-Bing and Cao, Dong-Sheng and Zhu, Min-Feng and Yun, Yong-Huan and Xiao, Nan and Liang, Yi-Zeng},
journal={Journal of Chemometrics},
volume={29},
number={7},
pages={389--398},
year={2015},
publisher={Wiley Online Library}
}
```