| ---
|
| license: unknown
|
| task_categories:
|
| - tabular-regression
|
| - graph-ml
|
| - tabular-classification
|
| tags:
|
| - chemistry
|
| - biology
|
| - medical
|
| - solubility
|
| - molecular-property-prediction
|
| - drug-discovery
|
| - aurigene
|
| pretty_name: MoleculeNet ESOL
|
| size_categories:
|
| - 1K<n<10K
|
| configs:
|
| - config_name: default
|
| data_files:
|
| - split: train
|
| path: esol.csv
|
| ---
|
|
|
| <!-- aurigene-header -->
|
| > ### Mirrored by [Aurigene AI](https://huggingface.co/Aurigene-AI)
|
| > **Discovery stage:** Lead optimization
|
| >
|
| > Aqueous solubility (log mol/L) for small organic molecules. Regression, the standard solubility benchmark.
|
| >
|
| > **Rows:** 1,128 (esol.csv 1,128)
|
| >
|
| > Pairs with [`Aurigene-AI/MoLFormer-XL-both-10pct`](https://huggingface.co/Aurigene-AI/MoLFormer-XL-both-10pct) from our model catalogue.
|
| >
|
| > Upstream: [`scikit-fingerprints/MoleculeNet_ESOL`](https://huggingface.co/datasets/scikit-fingerprints/MoleculeNet_ESOL) - all credit to the original authors and to the researchers who produced the underlying data; the dataset card and licence below are theirs.
|
| >
|
| > Explore the rest of the catalogue: [Molecule Explorer](https://huggingface.co/spaces/Aurigene-AI/molecule-explorer) - [Protein Target Explorer](https://huggingface.co/spaces/Aurigene-AI/protein-target-explorer) - [Drug Discovery Model Hub](https://huggingface.co/spaces/Aurigene-AI/drug-discovery-model-hub)
|
|
|
| ---
|
|
|
| # MoleculeNet ESOL
|
|
|
| ESOL (Estimated SOLubility) dataset [[1]](#1), part of MoleculeNet [[2]](#2) benchmark. It is intended to be used through
|
| [scikit-fingerprints](https://github.com/scikit-fingerprints/scikit-fingerprints) library.
|
|
|
| The task is to predict aqueous solubility. Targets are log-transformed, and the unit is log mols per litre (log Mol/L).
|
|
|
| | **Characteristic** | **Description** |
|
| |:------------------:|:---------------:|
|
| | Tasks | 1 |
|
| | Task type | regression |
|
| | Total samples | 1128 |
|
| | Recommended split | scaffold |
|
| | Recommended metric | RMSE |
|
|
|
| ## References
|
| <a id="1">[1]</a>
|
| John S. Delaney
|
| "ESOL: Estimating Aqueous Solubility Directly from Molecular Structure"
|
| J. Chem. Inf. Comput. Sci. 2004, 44, 3, 1000–1005
|
| https://pubs.acs.org/doi/10.1021/ci034243x
|
|
|
| <a id="2">[2]</a>
|
| Wu, Zhenqin, et al.
|
| "MoleculeNet: a benchmark for molecular machine learning."
|
| Chemical Science 9.2 (2018): 513-530
|
| https://pubs.rsc.org/en/content/articlelanding/2018/sc/c7sc02664a |
