mlsanityData to 7 Oct 2026

AlphaDesign: A graph protein design method and benchmark on AlphaFoldDB

arXiv 2202.01079 ↗First posted 1 Feb 2022q-bio.QM cs.AI cs.LGcited by 39

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Abstract (arXiv)

While DeepMind has tentatively solved protein folding, its inverse problem -- protein design which predicts protein sequences from their 3D structures -- still faces significant challenges. Particularly, the lack of large-scale standardized benchmark and poor accuray hinder the research progress. In order to standardize comparisons and draw more research interest, we use AlphaFold DB, one of the world's largest protein structure databases, to establish a new graph-based benchmark -- AlphaDesign. Based on AlphaDesign, we propose a new method called ADesign to improve accuracy by introducing protein angles as new features, using a simplified graph transformer encoder (SGT), and proposing a confidence-aware protein decoder (CPD). Meanwhile, SGT and CPD also improve model efficiency by simplifying the training and testing procedures. Experiments show that ADesign significantly outperforms previous graph models, e.g., the average accuracy is improved by 8%, and the inference speed is 40+ times faster than before.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Builds on 10 of its 28 references that are in the map. First posted on arXiv 1 Feb 2022.

Builds on

10 of 28 references.

References · 10

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2017Graph Attention Networkscited by 8,854
  3. 2016Densely Connected Convolutional Networkscited by 6,691
  4. 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,085
  5. 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,571
  6. 2021E(n) Equivariant Graph Neural Networkscited by 951
  7. 2020SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networkscited by 602
  8. 2018Deep Learning on Graphs: A Surveycited by 393
  9. 2020Learning from Protein Structure with Geometric Vector Perceptronscited by 308
  10. 2021Rotation Invariant Graph Neural Networks using Spin Convolutionscited by 52

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 7; 2023: 13; 2024: 9; 2025: 7; 2026: 3.

39 papers.

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  1. 2022Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Modelscited by 97
  2. 2022Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learningcited by 84
  3. 2022PiFold: Toward effective and efficient protein inverse foldingcited by 82
  4. 2022Hard Sample Aware Network for Contrastive Deep Graph Clusteringcited by 61
  5. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Bindingcited by 58
  6. 2023Graph Denoising Diffusion for Inverse Protein Foldingcited by 44
  7. 2023Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaborationcited by 30
  8. 2024A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applicationscited by 28
  9. 2024FoldToken: Learning Protein Language via Vector Quantization and Beyondcited by 21
  10. 2022Protein Language Models and Structure Prediction: Connection and Progressioncited by 17
  11. 2023AbODE: Ab Initio Antibody Design using Conjoined ODEscited by 15
  12. 2023De novo protein design using geometric vector field networkscited by 14
27 more
  1. 2022CoSP: Co-supervised pretraining of pocket and ligandcited by 12
  2. 2023Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinementcited by 11
  3. 2023DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraintscited by 10
  4. 2025dyAb: Flow Matching for Flexible Antibody Design with AlphaFold-driven Pre-binding Antigencited by 10
  5. 2024UniIF: Unified Molecule Inverse Foldingcited by 9
  6. 2024Bridge-IF: Learning Inverse Protein Folding with Markov Bridgescited by 9
  7. 2023Cross-Gate MLP with Protein Complex Invariant Embedding is A One-Shot Antibody Designercited by 8
  8. 2023PrefixMol: Target- and Chemistry-aware Molecule Design via Prefix Embeddingcited by 7
  9. 2023RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Designcited by 6
  10. 2023Generative artificial intelligence for de novo protein designcited by 5
  11. 2023Progressive Multi-Modality Learning for Inverse Protein Foldingcited by 5
  12. 2024Mask prior-guided denoising diffusion improves inverse protein foldingcited by 5
  13. 2025ProtInvTree: Deliberate Protein Inverse Folding with Reward-guided Tree Searchcited by 5
  14. 2025Protein Inverse Folding From Structure Feedbackcited by 5
  15. 2023CCPL: Cross-modal Contrastive Protein Learningcited by 4
  16. 2025From Sentences to Sequences: Rethinking Languages in Biological Systemcited by 3
  17. 2024GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learningcited by 2
  18. 2024MetaEnzyme: Meta Pan-Enzyme Learning for Task-Adaptive Redesigncited by 2
  19. 2023Efficiently Predicting Protein Stability Changes Upon Single-point Mutation with Large Language Modelscited by 1
  20. 2024Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomoleculescited by 1
  21. 2025EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimizationcited by 1
  22. 2024Pan-protein Design Learning Enables Task-adaptive Generalization for Low-resource Enzyme Designcited by 0
  23. 2025AlphaFold Database Debiasing for Robust Inverse Foldingcited by 0
  24. 2025RadDiff: Retrieval-Augmented Denoising Diffusion for Protein Inverse Foldingcited by 0
  25. 2026RIGA-Fold: A General Framework for Protein Inverse Folding via Recurrent Interaction and Geometric Awarenesscited by 0
  26. 2026Refold: Refining Protein Inverse Folding with Efficient Structural Matching and Fusioncited by 0
  27. 2026SurfDesign: Effective Protein Design on Molecular Surfacescited by 0