mlsanityData to 7 Oct 2026

OpenProteinSet: Training data for structural biology at scale

arXiv 2308.05326 ↗First posted 10 Aug 2023q-bio.BM cs.LGcited by 8

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Abstract (arXiv)

Multiple sequence alignments (MSAs) of proteins encode rich biological information and have been workhorses in bioinformatic methods for tasks like protein design and protein structure prediction for decades. Recent breakthroughs like AlphaFold2 that use transformers to attend directly over large quantities of raw MSAs have reaffirmed their importance. Generation of MSAs is highly computationally intensive, however, and no datasets comparable to those used to train AlphaFold2 have been made available to the research community, hindering progress in machine learning for proteins. To remedy this problem, we introduce OpenProteinSet, an open-source corpus of more than 16 million MSAs, associated structural homologs from the Protein Data Bank, and AlphaFold2 protein structure predictions. We have previously demonstrated the utility of OpenProteinSet by successfully retraining AlphaFold2 on it. We expect OpenProteinSet to be broadly useful as training and validation data for 1) diverse tasks focused on protein structure, function, and design and 2) large-scale multimodal machine learning research.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 20 of its 85 references that are in the map. First posted on arXiv 10 Aug 2023.

Builds on

20 of 85 references.

References · 20

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8 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 3; 2026: 1.

8 papers.

  1. 2024AlphaFold Meets Flow Matching for Generating Protein Ensemblescited by 105
  2. 2024Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequencescited by 13
  3. 2024MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Trainingcited by 7
  4. 2025Computational Protein Science in the Era of Large Language Models (LLMs)cited by 6
  5. 2024OneProt: Towards Multi-Modal Protein Foundation Modelscited by 2
  6. 2025Lightweight MSA Design Advances Protein Folding From Evolutionary Embeddingscited by 1
  7. 2025Protein Folding with Neural Ordinary Differential Equationscited by 0
  8. 2026Evolution-Aware MSA Reasoning for Subsampling via Factor Graphscited by 0