mlsanityData to 7 Oct 2026

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge

arXiv 2402.11459 ↗First posted 18 Feb 2024q-bio.BM cs.AI cs.LGcited by 16

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Abstract (arXiv)

Accurate prediction of protein-ligand binding structures, a task known as molecular docking is crucial for drug design but remains challenging. While deep learning has shown promise, existing methods often depend on holo-protein structures (docked, and not accessible in realistic tasks) or neglect pocket sidechain conformations, leading to limited practical utility and unrealistic conformation predictions. To fill these gaps, we introduce an under-explored task, named flexible docking to predict poses of ligand and pocket sidechains simultaneously and introduce Re-Dock, a novel diffusion bridge generative model extended to geometric manifolds. Specifically, we propose energy-to-geometry mapping inspired by the Newton-Euler equation to co-model the binding energy and conformations for reflecting the energy-constrained docking generative process. Comprehensive experiments on designed benchmark datasets including apo-dock and cross-dock demonstrate our model's superior effectiveness and efficiency over current methods.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 23 of its 69 references that are in the map. First posted on arXiv 18 Feb 2024.

Builds on

23 of 69 references.

References · 23

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  4. 2021Diffusion Schr"odinger Bridge with Applications to Score-Based Generative Modelingcited by 594
  5. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 307
  6. 2022Torsional Diffusion for Molecular Conformer Generationcited by 262
  7. 2022e3nn: Euclidean Neural Networkscited by 171
  8. 2022Diffusion-based Molecule Generation with Informative Prior Bridgescited by 104
  9. 2021Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Dockingcited by 81
  10. 2022Conditional Antibody Design as 3D Equivariant Graph Translationcited by 75
  11. 2023Non-Denoising Forward-Time Diffusionscited by 75
  12. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Bindingcited by 58
11 more
  1. 2022State-specific protein-ligand complex structure prediction with a multi-scale deep generative modelcited by 35
  2. 2023Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaborationcited by 30
  3. 2023Quantifying the Knowledge in GNNs for Reliable Distillation into MLPscited by 25
  4. 2023Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Frameworkcited by 24
  5. 2023DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packingcited by 24
  6. 2023Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equationcited by 18
  7. 2023Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Predictioncited by 13
  8. 2023Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoycited by 10
  9. 2022Non-equispaced Fourier Neural Solvers for PDEscited by 8
  10. 2022Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillationcited by 6
  11. 2021APObind: A Dataset of Ligand Unbound Protein Conformations for Machine Learning Applications in De Novo Drug Designcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 10; 2026: 3.

16 papers.

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  1. 2024A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applicationscited by 28
  2. 2024Diffusion Models in textitDe Novo Drug Designcited by 26
  3. 2024CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graphcited by 19
  4. 2025Energy-Based Flow Matching for Generating 3D Molecular Structurecited by 4
  5. 2025Unraveling the Potential of Diffusion Models in Small Molecule Generationcited by 3
  6. 2025SigmaDock: Untwisting Molecular Docking With Fragment-Based SE(3) Diffusioncited by 3
  7. 2025Departures: Distributional Transport for Single-Cell Perturbation Prediction with Neural Schr"odinger Bridgescited by 3
  8. 2025Fast and Accurate Blind Flexible Dockingcited by 2
  9. 2025Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flowscited by 2
  10. 2025Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modelingcited by 2
  11. 2025AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregationcited by 2
  12. 2025The Docking Game: Loop Self-Play for Fast, Dynamic, and Accurate Prediction of Flexible Protein-Ligand Bindingcited by 1
4 more
  1. 2026PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documentscited by 1
  2. 2025PocketVina Enables Scalable and Highly Accurate Physically Valid Docking through Multi-Pocket Conditioningcited by 0
  3. 2026Co-Diffusion: An Affinity-Aware Two-Stage Latent Diffusion Framework for Generalizable Drug-Target Affinity Predictioncited by 0
  4. 2026Harmonic Torsional Diffusion for Protein-Ligand Flexible Dockingcited by 0