Datasets:
File size: 1,481 Bytes
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---
license: mit
dataset_info:
features:
- name: clean_smiles
dtype: string
- name: id
dtype: string
- name: value
dtype: float64
- name: scaffold
dtype: string
splits:
- name: train
num_bytes: 1412399638
num_examples: 12378792
- name: validation
num_bytes: 175994570
num_examples: 1547349
- name: test
num_bytes: 171911605
num_examples: 1547350
download_size: 739740891
dataset_size: 1760305813
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
language:
- en
tags:
- chemistry
- biology
- virtual-screening
- docking
- drug-discovery
- machine-learning
- structure-based-design
pretty_name: RO4 Virtual Screening – d2 Target
size_categories:
- 10M<n<100M
description: >
This dataset contains docking scores for over 15 million compounds from the Enamine REAL library
screened against the d2 protein target using structure-based virtual screening. The data was
originally published by Luttens et al. (2022), and includes sanitized SMILES strings, compound
identifiers, docking scores, and Bemis-Murcko scaffolds. The dataset is split using scaffold-based
splitting to support robust machine learning benchmarking.
title: RO4 Virtual Screening Dataset for d2 Target
authors:
- Luttens et al.
date: 2025-03-13T00:00:00.000Z
doi: 10.1038/s43588-025-00777-x
---
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