NucleusDiff

Manifold-Constrained Nucleus-Level Denoising Diffusion Model
for Structure-Based Drug Design

Official pretrained checkpoint and data artifacts for the PNAS 2025 paper.

Caltech News Project Page PNAS Paper arXiv Source code Zenodo DOI Join SciGenAI on Slack

NucleusDiff model, data, and community

Shengchao Liu*, Liang Yan*, Weitao Du, Weiyang Liu, Zhuoxinran Li, Hongyu Guo,
Christian Borgs, Jennifer Chayes, Anima Anandkumar

Proceedings of the National Academy of Sciences (PNAS), 2025
*Equal contribution


✨ Overview

NucleusDiff is a physics-informed diffusion model for structure-based drug design. It constrains generated atomic nuclei with sampled points on electron-cloud manifolds, incorporating van der Waals spatial boundaries to reduce atomic collisions while preserving strong binding affinity.

This Hugging Face repository is the official mirror for the pretrained checkpoint and project data artifacts. For installation, training, inference, and evaluation, see the NucleusDiff source repository.

πŸ“¦ Repository Contents

Resource Location Description
🧠 Pretrained model model/ Official NucleusDiff checkpoint
🧬 Project data data/ Training, evaluation, and therapeutic-target artifacts
πŸ’» Implementation GitHub Source code, configuration, and usage instructions

Model

  • model/nucleusdiff_pretrained_model.pt β€” pretrained NucleusDiff checkpoint.

Data

  • data/crossdocked_v1.1_rmsd1.0_pocket10_processed_w_manifold_data_version.lmdb β€” preprocessed CrossDocked manifold dataset.
  • data/crossdocked_pocket10_pose_w_manifold_data_split.pt β€” train/validation/test split used by NucleusDiff.
  • data/crossdocked_v1.1_rmsd1.0.tar.gz β€” filtered CrossDocked data.
  • data/split_by_name.pt β€” reference CrossDocked split.
  • data/test_set.zip β€” protein test set used for docking evaluation.
  • data/real_world.zip β€” therapeutic-target evaluation data.
  • data/affinity_info.pkl β€” affinity metadata.
  • data/test_vina_crossdock_dict.pkl β€” CrossDocked Vina evaluation metadata.

⬇️ Download

Install or update the Hugging Face CLI:

pip install -U huggingface_hub

Download only the pretrained model:

hf download LiangYan3612/NucleusDiff \
  --include "model/*" \
  --local-dir ./NucleusDiff_artifacts

Download all data files:

hf download LiangYan3612/NucleusDiff \
  --include "data/*" \
  --local-dir ./NucleusDiff_artifacts

Download the complete model-and-data snapshot:

hf download LiangYan3612/NucleusDiff \
  --local-dir ./NucleusDiff_artifacts

πŸ’¬ Community

Join the SciGenAI Slack community for the dedicated NucleusDiff channel, real-time questions, code contributions, pull requests, and collaboration across generative AI for science.

πŸ“œ License and Data Provenance

The NucleusDiff source code is released under the MIT License. Included data artifacts are mirrors of the files used by the project and may remain subject to the terms of their original data sources.

πŸ“– Citation

@article{liu2025manifold,
  title={Manifold-constrained nucleus-level denoising diffusion model for structure-based drug design},
  author={Liu, Shengchao and Yan, Liang and Du, Weitao and Liu, Weiyang and Li, Zhuoxinran and Guo, Hongyu and Borgs, Christian and Chayes, Jennifer and Anandkumar, Anima},
  journal={Proceedings of the National Academy of Sciences},
  volume={122},
  number={41},
  pages={e2415666122},
  year={2025},
  publisher={National Academy of Sciences}
}
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