README.md

metadata

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