mlsanityData to 7 Oct 2026

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

arXiv 2210.01776 ↗First posted 4 Oct 2022q-bio.BM cs.LG physics.bio-phcited by 307

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Cited by 113 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Predicting the binding structure of a small molecule ligand to a protein -- a task known as molecular docking -- is critical to drug design. Recent deep learning methods that treat docking as a regression problem have decreased runtime compared to traditional search-based methods but have yet to offer substantial improvements in accuracy. We instead frame molecular docking as a generative modeling problem and develop DiffDock, a diffusion generative model over the non-Euclidean manifold of ligand poses. To do so, we map this manifold to the product space of the degrees of freedom (translational, rotational, and torsional) involved in docking and develop an efficient diffusion process on this space. Empirically, DiffDock obtains a 38% top-1 success rate (RMSD<2A) on PDBBind, significantly outperforming the previous state-of-the-art of traditional docking (23%) and deep learning (20%) methods. Moreover, while previous methods are not able to dock on computationally folded structures (maximum accuracy 10.4%), DiffDock maintains significantly higher precision (21.7%). Finally, DiffDock has fast inference times and provides confidence estimates with high selective accuracy.

Key facts. Cited by 307 papers in the map (data through 7 Oct 2026). Builds on 17 of its 53 references that are in the map. First posted on arXiv 4 Oct 2022.

Builds on

17 of 53 references.

References · 17

  1. 2017Attention Is All You Needcited by 59,932
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  5. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 735
  6. 2022Equivariant Diffusion for Molecule Generation in 3Dcited by 666
  7. 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactionscited by 569
  8. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generationcited by 511
  9. 2020Principal Neighbourhood Aggregation for Graph Netscited by 477
  10. 2022Torsional Diffusion for Molecular Conformer Generationcited by 262
  11. 2022Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problemcited by 229
  12. 2022Riemannian Score-Based Generative Modellingcited by 216
5 more
  1. 2022e3nn: Euclidean Neural Networkscited by 171
  2. 2022EquiBind: Geometric Deep Learning for Drug Binding Structure Predictioncited by 143
  3. 2022Multi-Scale Representation Learning on Proteinscited by 52
  4. 2020PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictionscited by 31
  5. 2018Functional Maps Representation on Product Manifoldscited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 10; 2023: 80; 2024: 85; 2025: 81; 2026: 51.

307 papers.

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  1. 2023Improving and generalizing flow-based generative models with minibatch optimal transportcited by 835
  2. 2023SE(3) diffusion model with application to protein backbone generationcited by 214
  3. 2022Structure-based Drug Design with Equivariant Diffusion Modelscited by 213
  4. 2023DDP: Diffusion Model for Dense Visual Predictioncited by 148
  5. 2022An optimal control perspective on diffusion-based generative modelingcited by 145
  6. 2023Crystal Structure Prediction by Joint Equivariant Diffusioncited by 142
  7. 2024Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planningcited by 135
  8. 2024Unlocking Guidance for Discrete State-Space Diffusion and Flow Modelscited by 124
  9. 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Designcited by 121
  10. 2023MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generationcited by 96
  11. 2024Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generationcited by 85
  12. 2025Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Reviewcited by 82
38 more
  1. 2023Generative Diffusion Models on Graphs: Methods and Applicationscited by 79
  2. 2023SODA: Bottleneck Diffusion Models for Representation Learningcited by 76
  3. 2025All-atom Diffusion Transformers: Unified generative modelling of molecules and materialscited by 75
  4. 2023Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-Type Samplerscited by 73
  5. 2023Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamicscited by 72
  6. 2023Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Modelscited by 65
  7. 2023A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systemscited by 65
  8. 2023EigenFold: Generative Protein Structure Prediction with Diffusion Modelscited by 63
  9. 2023Diffusion Models for Constrained Domainscited by 60
  10. 2023One-Step Diffusion Distillation via Deep Equilibrium Modelscited by 60
  11. 2023Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistentcited by 58
  12. 2023Swallowing the Bitter Pill: Simplified Scalable Conformer Generationcited by 55
  13. 2023Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulationcited by 51
  14. 2023How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Controlcited by 50
  15. 2023Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generationcited by 50
  16. 2024How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunitiescited by 50
  17. 2023Closed-Form Diffusion Modelscited by 46
  18. 2025Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraintscited by 46
  19. 2023Graph Denoising Diffusion for Inverse Protein Foldingcited by 44
  20. 2022Categorical SDEs with Simplex Diffusioncited by 42
  21. 2024Equivariant Frames and the Impossibility of Continuous Canonicalizationcited by 41
  22. 2022Structure-based drug design with geometric deep learningcited by 40
  23. 2024Learning to Discretize Denoising Diffusion ODEscited by 39
  24. 2024Efficient Diffusion Models: A Comprehensive Survey from Principles to Practicescited by 39
  25. 2023Aligned Diffusion Schr"odinger Bridgescited by 38
  26. 2023Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltoniancited by 38
  27. 20233D molecule generation by denoising voxel gridscited by 38
  28. 2023Mirror Diffusion Models for Constrained and Watermarked Generationcited by 38
  29. 2023Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasetscited by 37
  30. 2022Fast Graph Generation via Spectral Diffusioncited by 36
  31. 2023Geometry-Complete Diffusion for 3D Molecule Generation and Optimizationcited by 36
  32. 2024On the Scalability of GNNs for Molecular Graphscited by 36
  33. 2023RetroBridge: Modeling Retrosynthesis with Markov Bridgescited by 35
  34. 2023A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Materialcited by 34
  35. 2025MagicMirror: ID-Preserved Video Generation in Video Diffusion Transformerscited by 32
  36. 2023Interactive Natural Language Processingcited by 31
  37. 2024DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassemblycited by 31
  38. 2023Accurate transition state generation with an object-aware equivariant elementary reaction diffusion modelcited by 30

50 most cited of 307 All 307 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2022DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations
  2. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
  3. 2024Bridging the Gap between Learning and Inference for Diffusion-Based Molecule Generation
  4. 2025Generating 3D Binding Molecules Using Shape-Conditioned Diffusion Models with Guidance
  5. 2025BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation
  6. 2024Binding-Adaptive Diffusion Models for Structure-Based Drug Design
  7. 2024Physics-informed generative model for drug-like molecule conformers
  8. 2024Diffusion Models in textitDe Novo Drug Design