{"id":13478528,"url":"https://github.com/aqlaboratory/openfold","last_synced_at":"2025-10-08T17:22:51.768Z","repository":{"id":37073111,"uuid":"406555580","full_name":"aqlaboratory/openfold","owner":"aqlaboratory","description":"Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2","archived":false,"fork":false,"pushed_at":"2025-02-24T03:36:56.000Z","size":19952,"stargazers_count":2985,"open_issues_count":208,"forks_count":587,"subscribers_count":47,"default_branch":"main","last_synced_at":"2025-04-23T21:44:03.626Z","etag":null,"topics":["alphafold2","protein-structure","pytorch"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/aqlaboratory.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2021-09-14T23:59:02.000Z","updated_at":"2025-04-23T03:15:41.000Z","dependencies_parsed_at":"2023-09-22T05:53:42.331Z","dependency_job_id":"5a966055-bcd3-4b68-80d4-1c625a67309c","html_url":"https://github.com/aqlaboratory/openfold","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aqlaboratory%2Fopenfold","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aqlaboratory%2Fopenfold/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aqlaboratory%2Fopenfold/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aqlaboratory%2Fopenfold/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aqlaboratory","download_url":"https://codeload.github.com/aqlaboratory/openfold/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253969266,"owners_count":21992264,"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":["alphafold2","protein-structure","pytorch"],"created_at":"2024-07-31T16:01:58.291Z","updated_at":"2025-10-08T17:22:51.668Z","avatar_url":"https://github.com/aqlaboratory.png","language":"Python","readme":"![header ](imgs/of_banner.png)\n_Figure: Comparison of OpenFold and AlphaFold2 predictions to the experimental structure of PDB 7KDX, chain B._\n\n# OpenFold\n\nA faithful but trainable PyTorch reproduction of DeepMind's \n[AlphaFold 2](https://github.com/deepmind/alphafold).\n\n# Documentation\nSee our new home for docs at [openfold.readthedocs.io](https://openfold.readthedocs.io/en/latest/), with instructions for installation and model inference/training.\n\nMuch of the content from this page may be found [here.](https://github.com/aqlaboratory/openfold/blob/main/docs/source/original_readme.md)\n\n## Copyright Notice\n\nWhile AlphaFold's and, by extension, OpenFold's source code is licensed under\nthe permissive Apache Licence, Version 2.0, DeepMind's pretrained parameters \nfall under the CC BY 4.0 license, a copy of which is downloaded to \n`openfold/resources/params` by the installation script. Note that the latter\nreplaces the original, more restrictive CC BY-NC 4.0 license as of January 2022.\n\n## Contributing\n\nIf you encounter problems using OpenFold, feel free to create an issue! We also\nwelcome pull requests from the community.\n\n## Citing this Work\n\nPlease cite our paper:\n\n```bibtex\n@article {Ahdritz2022.11.20.517210,\n\tauthor = {Ahdritz, Gustaf and Bouatta, Nazim and Floristean, Christina and Kadyan, Sachin and Xia, Qinghui and Gerecke, William and O{\\textquoteright}Donnell, Timothy J and Berenberg, Daniel and Fisk, Ian and Zanichelli, Niccolò and Zhang, Bo and Nowaczynski, Arkadiusz and Wang, Bei and Stepniewska-Dziubinska, Marta M and Zhang, Shang and Ojewole, Adegoke and Guney, Murat Efe and Biderman, Stella and Watkins, Andrew M and Ra, Stephen and Lorenzo, Pablo Ribalta and Nivon, Lucas and Weitzner, Brian and Ban, Yih-En Andrew and Sorger, Peter K and Mostaque, Emad and Zhang, Zhao and Bonneau, Richard and AlQuraishi, Mohammed},\n\ttitle = {{O}pen{F}old: {R}etraining {A}lpha{F}old2 yields new insights into its learning mechanisms and capacity for generalization},\n\telocation-id = {2022.11.20.517210},\n\tyear = {2022},\n\tdoi = {10.1101/2022.11.20.517210},\n\tpublisher = {Cold Spring Harbor Laboratory},\n\tURL = {https://www.biorxiv.org/content/10.1101/2022.11.20.517210},\n\teprint = {https://www.biorxiv.org/content/early/2022/11/22/2022.11.20.517210.full.pdf},\n\tjournal = {bioRxiv}\n}\n```\nIf you use OpenProteinSet, please also cite:\n\n```bibtex\n@misc{ahdritz2023openproteinset,\n      title={{O}pen{P}rotein{S}et: {T}raining data for structural biology at scale}, \n      author={Gustaf Ahdritz and Nazim Bouatta and Sachin Kadyan and Lukas Jarosch and Daniel Berenberg and Ian Fisk and Andrew M. Watkins and Stephen Ra and Richard Bonneau and Mohammed AlQuraishi},\n      year={2023},\n      eprint={2308.05326},\n      archivePrefix={arXiv},\n      primaryClass={q-bio.BM}\n}\n```\nAny work that cites OpenFold should also cite [AlphaFold](https://www.nature.com/articles/s41586-021-03819-2) and [AlphaFold-Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1) if applicable.\n","funding_links":[],"categories":["Python","Structure prediction","Other Machine Learning Applications","蛋白质结构","NLP","Machine Learning Tasks and Models","Uncategorized","Ranked by starred repositories"],"sub_categories":["Others","网络服务_其他","3. Pretraining","Foundation Models","Uncategorized"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faqlaboratory%2Fopenfold","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faqlaboratory%2Fopenfold","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faqlaboratory%2Fopenfold/lists"}