{"id":13958598,"url":"https://github.com/luost26/3D-Generative-SBDD","last_synced_at":"2025-07-21T00:31:20.478Z","repository":{"id":40624129,"uuid":"421004583","full_name":"luost26/3D-Generative-SBDD","owner":"luost26","description":"💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)","archived":true,"fork":false,"pushed_at":"2023-02-12T03:41:05.000Z","size":4808,"stargazers_count":189,"open_issues_count":6,"forks_count":46,"subscribers_count":15,"default_branch":"main","last_synced_at":"2025-05-12T00:35:05.627Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/luost26.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-10-25T11:57:45.000Z","updated_at":"2025-04-24T08:26:11.000Z","dependencies_parsed_at":"2024-11-18T01:47:08.167Z","dependency_job_id":null,"html_url":"https://github.com/luost26/3D-Generative-SBDD","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/luost26/3D-Generative-SBDD","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/luost26%2F3D-Generative-SBDD","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/luost26%2F3D-Generative-SBDD/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/luost26%2F3D-Generative-SBDD/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/luost26%2F3D-Generative-SBDD/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/luost26","download_url":"https://codeload.github.com/luost26/3D-Generative-SBDD/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/luost26%2F3D-Generative-SBDD/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266221260,"owners_count":23894965,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-08T13:01:45.900Z","updated_at":"2025-07-21T00:31:15.457Z","avatar_url":"https://github.com/luost26.png","language":"Python","funding_links":[],"categories":["4. Structure-Based *De Novo* Drug Design with Deep Generative Models \u003ca name=\"4\"\u003e\u003c/a\u003e","药物发现、药物设计"],"sub_categories":["4.1 Structure-based de novo drug design methods \u003ca name=\"4.1\"\u003e\u003c/a\u003e","网络服务_其他"],"readme":"# A 3D Generative Model for Structure-Based Drug Design\n\n\u003cimg src=\"./assets/teaser.png\" alt=\"teaser\" /\u003e\n\n[[Paper](https://arxiv.org/abs/2203.10446)]\n[[Slides](https://drive.google.com/file/d/1PnypgrWqZAnaONy_Ccq-fmTDo4IRJpX1/view?usp=sharing)]\n\n## 📢 News\n\n- Please check out our latest work on structure-based drug design: *Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets* (ICML 2022)\n  - Code: https://github.com/pengxingang/Pocket2Mol\n  - Paper: https://arxiv.org/abs/2205.07249\n\n## Installation\n\n### Dependency\n\nThe code has been tested in the following environment:\n\n| Package           | Version   |\n|-|-|\n| Python            | 3.8.12    |\n| PyTorch           | 1.10.1    |\n| CUDA              | 11.3.1    |\n| PyTorch Geometric | 2.0.3     |\n| RDKit             | 2020.09.5 |\n| OpenBabel         | 3.1.0     |\n| BioPython         | 1.79      |\n\n### Install via Conda YML FIle (CUDA 11.3)\n```bash\nconda env create -f env_cuda113.yml\nconda activate SBDD-3D\n```\n\n### Install Manually\n```bash\nconda create --name SBDD-3D python=3.8\nconda activate SBDD-3D\n\nconda install pytorch=1.10.1 torchvision torchaudio cudatoolkit=11.3 -c pytorch\nconda install pyg -c pyg -c conda-forge\nconda install easydict -c conda-forge\nconda install biopython -c conda-forge\nconda install rdkit openbabel python-lmdb -c conda-forge\nconda install tensorboard -c conda-forge\n```\n\n## Datasets\n\nPlease refer to [`README.md`](./data/README.md) in the `data` folder.\n\n## Sampling\n\n### Sampling for Pockets in the Testset\nTo sample molecules for the i-th pocket in the testset, please first download the trained models following \n[`README.md`](./pretrained/README.md) in the `pretrained` folder. Then, run the following command:\n```bash\npython sample.py ./configs/sample.yml --data_id {i}  # Replace {i} with the index of the data. i is between 0 and 99 for the testset.\n```\n\n### Sampling for PDB Structures\n\nTo generate ligands for your own pocket, you need to provide the `PDB` structure file of the protein, the center coordinate of the pocket bounding box, and optionally the side length of the bounding box (default: 22Å).\n\nExample:\n```bash\npython sample_for_pdb.py \\\n    --pdb_path ./example/4yhj.pdb \\\n    --center 32.0,28.0,36.0\n```\n\n\u003cimg src=\"./assets/bounding_box.png\" alt=\"bounding box\" width=\"70%\" /\u003e\n\n## Training\n\nThe open source repo of our latest work [Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets](https://arxiv.org/abs/2205.07249) (ICML 2022) is tested for training. \nYou may check it out here: https://github.com/pengxingang/Pocket2Mol\n\n\n## Citation\n\n```\n@inproceedings{luo2021sbdd,\n    title={A 3D Generative Model for Structure-Based Drug Design},\n    author={Shitong Luo and Jiaqi Guan and Jianzhu Ma and Jian Peng},\n    booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},\n    year={2021}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fluost26%2F3D-Generative-SBDD","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fluost26%2F3D-Generative-SBDD","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fluost26%2F3D-Generative-SBDD/lists"}