---
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
---