---
license: unknown
task_categories:
- tabular-classification
- graph-ml
- text-classification
tags:
- chemistry
- biology
- medical
- binding-affinity-prediction
- molecular-property-prediction
- drug-discovery
- aurigene
pretty_name: MoleculeNet BACE
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: train
    path: bace.csv
---

<!-- aurigene-header -->
> ### Mirrored by [Aurigene AI](https://huggingface.co/Aurigene-AI)
> **Discovery stage:** Lead optimization
>
> BACE-1 (beta-secretase 1) inhibition, a validated Alzheimer's disease target. Binary classification.
>
> **Rows:** 1,513 (bace.csv 1,513)
>
> Pairs with [`Aurigene-AI/ChemBERTa-77M-MTR`](https://huggingface.co/Aurigene-AI/ChemBERTa-77M-MTR) from our model catalogue.
>
> Upstream: [`scikit-fingerprints/MoleculeNet_BACE`](https://huggingface.co/datasets/scikit-fingerprints/MoleculeNet_BACE) - 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 BACE

BACE 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 binding results for a set of inhibitors of humanβ-secretase 1 (BACE-1).

| **Characteristic** | **Description** |
|:------------------:|:---------------:|
|        Tasks       |        1        |
|      Task type     |  classification |
|    Total samples   |       1513      |
|  Recommended split |     scaffold    |
| Recommended metric |      AUROC      |

## References
<a id="1">[1]</a> 
Govindan Subramanian et al.
"Computational Modeling of β-Secretase 1 (BACE-1) Inhibitors Using
Ligand Based Approaches"
J. Chem. Inf. Model. 2016, 56, 10, 1936–1949
https://pubs.acs.org/doi/10.1021/acs.jcim.6b00290

<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