| license: cc0-1.0 | |
| task_categories: | |
| - tabular-regression | |
| - graph-ml | |
| - text-classification | |
| tags: | |
| - chemistry | |
| - biology | |
| - medical | |
| pretty_name: ASAP-OpenADMET LogD | |
| size_categories: | |
| - n<1K | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: "logd.csv" | |
| # ASAP-OpenADMET LogD | |
| ASAP_OpenADMET_LogD dataset from the ASAP Discovery-OpenADMET Antiviral Drug Discovery Challenge [[1]](#1) [[2]](#2) [[3]](#3). It is intended to be used through | |
| [scikit-fingerprints](https://github.com/scikit-fingerprints/scikit-fingerprints) library. | |
| The task is to predict LogD (distribution coefficient) of molecules. | |
| | **Characteristic** | **Description** | | |
| |:------------------:|:---------------:| | |
| | Tasks | 1 | | |
| | Task type | regression | | |
| | Total samples | 478 | | |
| | Recommended split | time | | |
| | Recommended metric | MAE | | |
| ## References | |
| <a id="1">[1]</a> | |
| ASAP Discovery | |
| "ASAP Discovery x OpenADMET Antiviral Drug Discovery Challenge" | |
| https://polarishub.io/blog/antiviral-competition | |
| <a id="2">[2]</a> | |
| Chodera et al. | |
| "The ASAP Discovery Antiviral Drug Discovery Challenge" | |
| https://doi.org/10.26434/chemrxiv-2025-zd9mr | |
| <a id="3">[3]</a> | |
| MacDermott-Opeskin, Hugo, et al. | |
| "A computational community blind challenge on pan-coronavirus drug discovery data" | |
| J. Chem. Inf. Model. 2026, 66, 6, 3129-3149 | |
| https://doi.org/10.1021/acs.jcim.5c02106 | |