{"url":"/task/protein-structure-prediction","name":"Protein Structure Prediction","slug":"protein-structure-prediction","description_markdown":"Image credit: [FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours](https://arxiv.org/pdf/2203.00854v1.pdf)","categories":[{"name":"Medical","url":"/area/medical"},{"name":"Miscellaneous","url":"/area/miscellaneous"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":188,"papers_with_code":67,"benchmarks":4,"benchmark_tables_in_archive":4,"benchmark_tables_shown":4,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":2,"subtasks":2,"parent_tasks":0},"benchmarks":[{"leaderboard":"/sota/protein-structure-prediction-on-caspseq","slug":"protein-structure-prediction-on-caspseq","dataset":"CASPSeq","dataset_url":null,"rows_in_archive":5,"metrics":["Validation perplexity"],"first_row_in_archive_order":{"model":"GAL 120B","paper_title":"Galactica: A Large Language Model for Science","paper_url":"/paper/galactica-a-large-language-model-for-science-1","paper_date":"2022-11-16","arxiv_id":"2211.09085","code_links":[{"title":"paperswithcode/galai","url":"https://github.com/paperswithcode/galai"}],"syntology":{"n":2,"n_ran":0,"n_unverified":2,"n_pointer_only":0}}},{"leaderboard":"/sota/protein-structure-prediction-on-caspsimseq","slug":"protein-structure-prediction-on-caspsimseq","dataset":"CASPSimSeq","dataset_url":null,"rows_in_archive":5,"metrics":["Validation perplexity"],"first_row_in_archive_order":{"model":"GAL 120B","paper_title":"Galactica: A Large Language Model for Science","paper_url":"/paper/galactica-a-large-language-model-for-science-1","paper_date":"2022-11-16","arxiv_id":"2211.09085","code_links":[{"title":"paperswithcode/galai","url":"https://github.com/paperswithcode/galai"}],"syntology":{"n":2,"n_ran":0,"n_unverified":2,"n_pointer_only":0}}},{"leaderboard":"/sota/protein-structure-prediction-on-paenseq","slug":"protein-structure-prediction-on-paenseq","dataset":"PaenSeq","dataset_url":null,"rows_in_archive":5,"metrics":["Validation perplexity"],"first_row_in_archive_order":{"model":"GAL 120B","paper_title":"Galactica: A Large Language Model for Science","paper_url":"/paper/galactica-a-large-language-model-for-science-1","paper_date":"2022-11-16","arxiv_id":"2211.09085","code_links":[{"title":"paperswithcode/galai","url":"https://github.com/paperswithcode/galai"}],"syntology":{"n":2,"n_ran":0,"n_unverified":2,"n_pointer_only":0}}},{"leaderboard":"/sota/protein-structure-prediction-on-uniprotseq","slug":"protein-structure-prediction-on-uniprotseq","dataset":"UniProtSeq","dataset_url":null,"rows_in_archive":5,"metrics":["Validation perplexity"],"first_row_in_archive_order":{"model":"GAL 120B","paper_title":"Galactica: A Large Language Model for Science","paper_url":"/paper/galactica-a-large-language-model-for-science-1","paper_date":"2022-11-16","arxiv_id":"2211.09085","code_links":[{"title":"paperswithcode/galai","url":"https://github.com/paperswithcode/galai"}],"syntology":{"n":2,"n_ran":0,"n_unverified":2,"n_pointer_only":0}}}],"datasets":[{"url":"/dataset/sidechainnet","name":"SidechainNet","full_name":null,"num_papers_in_archive":1},{"url":"/dataset/cameo","name":"CAMEO","full_name":"Continuous automated model evaluation","num_papers_in_archive":0}],"subtasks":[{"url":"/task/protein-complex-prediction","name":"Protein complex prediction"},{"url":"/task/protein-interface-prediction","name":"Protein Interface Prediction"}],"parent_tasks":[],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":67,"tagged_in_all":188,"items":[{"url":"/paper/highly-accurate-protein-structure-prediction","title":"Highly accurate protein structure prediction with AlphaFold","date":"2021-07-15","arxiv_id":null,"repositories_listed":5,"syntology":null},{"url":"/paper/se-3-diffusion-model-with-application-to","title":"SE(3) diffusion model with application to protein backbone generation","date":"2023-02-05","arxiv_id":"2302.02277","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":1}},{"url":"/paper/distribution-free-risk-controlling-prediction","title":"Distribution-Free, Risk-Controlling Prediction Sets","date":"2021-01-07","arxiv_id":"2101.02703","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":0}},{"url":"/paper/sidechainnet-an-all-atom-protein-structure","title":"SidechainNet: An All-Atom Protein Structure Dataset for Machine Learning","date":"2020-10-16","arxiv_id":"2010.08162","repositories_listed":3,"syntology":{"n":12,"n_ran":4,"n_unverified":8,"n_pointer_only":0}},{"url":"/paper/accurate-protein-structure-prediction-by","title":"Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations","date":"2019-11-09","arxiv_id":"1911.05531","repositories_listed":3,"syntology":null},{"url":"/paper/must-cnn-a-multilayer-shift-and-stitch-deep","title":"MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure Prediction","date":"2016-05-10","arxiv_id":"1605.03004","repositories_listed":3,"syntology":null},{"url":"/paper/atomsurf-surface-representation-for-learning","title":"AtomSurf : Surface Representation for Learning on Protein Structures","date":"2023-09-28","arxiv_id":"2309.16519","repositories_listed":2,"syntology":{"n":16,"n_ran":13,"n_unverified":3,"n_pointer_only":15}},{"url":"/paper/enhancing-the-protein-tertiary-structure","title":"Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation","date":"2023-06-02","arxiv_id":"2306.01824","repositories_listed":2,"syntology":null},{"url":"/paper/dynamic-backbone-protein-ligand-structure","title":"State-specific protein-ligand complex structure prediction with a multi-scale deep generative model","date":"2022-09-30","arxiv_id":"2209.15171","repositories_listed":2,"syntology":null},{"url":"/paper/few-shot-learning-of-accurate-folding","title":"Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure Prediction","date":"2022-08-20","arxiv_id":"2208.09652","repositories_listed":2,"syntology":{"n":12,"n_ran":2,"n_unverified":10,"n_pointer_only":2}},{"url":"/paper/psp-million-level-protein-sequence-dataset","title":"PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction","date":"2022-06-24","arxiv_id":"2206.12240","repositories_listed":2,"syntology":null},{"url":"/paper/proteinbert-a-universal-deep-learning-model","title":"ProteinBERT: a universal deep-learning model of protein sequence and function","date":"2022-02-10","arxiv_id":null,"repositories_listed":2,"syntology":null},{"url":"/paper/iterative-se-3-transformers","title":"Iterative SE(3)-Transformers","date":"2021-02-26","arxiv_id":"2102.13419","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_unverified":0,"n_pointer_only":2}},{"url":"/paper/proteinnet-a-standardized-data-set-for","title":"ProteinNet: a standardized data set for machine learning of protein structure","date":"2019-02-01","arxiv_id":"1902.00249","repositories_listed":2,"syntology":{"n":7,"n_ran":0,"n_unverified":7,"n_pointer_only":0}},{"url":"/paper/conformation-aware-structure-prediction-of","title":"Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins","date":"2025-07-11","arxiv_id":"2507.09054","repositories_listed":1,"syntology":null},{"url":"/paper/megafold-system-level-optimizations-for","title":"MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction Models","date":"2025-06-24","arxiv_id":"2506.20686","repositories_listed":1,"syntology":null},{"url":"/paper/psbench-a-large-scale-benchmark-for","title":"PSBench: a large-scale benchmark for estimating the accuracy of protein complex structural models","date":"2025-05-13","arxiv_id":"2505.22674","repositories_listed":1,"syntology":null},{"url":"/paper/towards-interpretable-protein-structure","title":"Towards Interpretable Protein Structure Prediction with Sparse Autoencoders","date":"2025-03-11","arxiv_id":"2503.08764","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_unverified":1,"n_pointer_only":4}},{"url":"/paper/protein-large-language-models-a-comprehensive","title":"Protein Large Language Models: A Comprehensive Survey","date":"2025-02-21","arxiv_id":"2502.17504","repositories_listed":1,"syntology":null},{"url":"/paper/motifbench-a-standardized-protein-design","title":"MotifBench: A standardized protein design benchmark for motif-scaffolding problems","date":"2025-02-18","arxiv_id":"2502.12479","repositories_listed":1,"syntology":null},{"url":"/paper/deep-learning-of-proteins-with-local-and","title":"Deep Learning of Proteins with Local and Global Regions of Disorder","date":"2025-02-17","arxiv_id":"2502.11326","repositories_listed":1,"syntology":null},{"url":"/paper/pymolfold-interactive-protein-and-ligand","title":"PyMOLfold: Interactive Protein and Ligand Structure Prediction in PyMOL","date":"2025-02-01","arxiv_id":"2502.00508","repositories_listed":1,"syntology":null},{"url":"/paper/human-genome-book-words-sentences-and","title":"Human Genome Book: Words, Sentences and Paragraphs","date":"2025-01-23","arxiv_id":"2501.16982","repositories_listed":1,"syntology":null},{"url":"/paper/generative-diffusion-model-with-inverse","title":"Generative diffusion model with inverse renormalization group flows","date":"2025-01-15","arxiv_id":"2501.09064","repositories_listed":1,"syntology":null},{"url":"/paper/training-on-test-proteins-improves-fitness","title":"Training on test proteins improves fitness, structure, and function prediction","date":"2024-11-04","arxiv_id":"2411.02109","repositories_listed":1,"syntology":null},{"url":"/paper/foldmark-protecting-protein-generative-models","title":"FoldMark: Protecting Protein Generative Models with Watermarking","date":"2024-10-27","arxiv_id":"2410.20354","repositories_listed":1,"syntology":null},{"url":"/paper/cpe-pro-a-structure-sensitive-deep-learning","title":"CPE-Pro: A Structure-Sensitive Deep Learning Method for Protein Representation and Origin Evaluation","date":"2024-10-21","arxiv_id":"2410.15592","repositories_listed":1,"syntology":null},{"url":"/paper/plddt-predictor-high-speed-protein-screening","title":"pLDDT-Predictor: High-speed Protein Screening Using Transformer and ESM2","date":"2024-10-11","arxiv_id":"2410.21283","repositories_listed":1,"syntology":null},{"url":"/paper/deepprotein-deep-learning-library-and","title":"DeepProtein: Deep Learning Library and Benchmark for Protein Sequence Learning","date":"2024-10-02","arxiv_id":"2410.02023","repositories_listed":1,"syntology":null},{"url":"/paper/msagpt-neural-prompting-protein-structure","title":"MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training","date":"2024-06-08","arxiv_id":"2406.05347","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_unverified":0,"n_pointer_only":0}}],"syntology_records":9,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}