mlsanityData to 7 Oct 2026

Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design

arXiv 2310.05764 ↗First posted 9 Oct 2023cs.LG cs.AIcited by 29

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Abstract (arXiv)

A significant amount of protein function requires binding small molecules, including enzymatic catalysis. As such, designing binding pockets for small molecules has several impactful applications ranging from drug synthesis to energy storage. Towards this goal, we first develop HarmonicFlow, an improved generative process over 3D protein-ligand binding structures based on our self-conditioned flow matching objective. FlowSite extends this flow model to jointly generate a protein pocket's discrete residue types and the molecule's binding 3D structure. We show that HarmonicFlow improves upon state-of-the-art generative processes for docking in simplicity, generality, and average sample quality in pocket-level docking. Enabled by this structure modeling, FlowSite designs binding sites substantially better than baseline approaches.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 33 of its 76 references that are in the map. First posted on arXiv 9 Oct 2023.

Builds on

33 of 76 references.

References · 33

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2022Flow Matching for Generative Modelingcited by 5,426
  5. 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,550
  6. 2022Building Normalizing Flows with Stochastic Interpolantscited by 964
  7. 2023Stochastic Interpolants: A Unifying Framework for Flows and Diffusionscited by 897
  8. 2023Improving and generalizing flow-based generative models with minibatch optimal transportcited by 835
  9. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 735
  10. 2021Diffusion Schr"odinger Bridge with Applications to Score-Based Generative Modelingcited by 594
  11. 2022DiGress: Discrete Denoising diffusion for graph generationcited by 503
  12. 2020Principal Neighbourhood Aggregation for Graph Netscited by 477
21 more
  1. 2022Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioningcited by 362
  2. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 307
  3. 2023Multisample Flow Matching: Straightening Flows with Minibatch Couplingscited by 267
  4. 2022Torsional Diffusion for Molecular Conformer Generationcited by 262
  5. 2021Likelihood Training of Schr"odinger Bridge using Forward-Backward SDEs Theorycited by 216
  6. 2023SE(3) diffusion model with application to protein backbone generationcited by 214
  7. 2022EquiBind: Geometric Deep Learning for Drug Binding Structure Predictioncited by 143
  8. 2023MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generationcited by 96
  9. 2022Action Matching: Learning Stochastic Dynamics from Samplescited by 94
  10. 2021Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-designcited by 82
  11. 2022PiFold: Toward effective and efficient protein inverse foldingcited by 82
  12. 2023Simulation-free Schr"odinger bridges via score and flow matchingcited by 81
  13. 2023EigenFold: Generative Protein Structure Prediction with Diffusion Modelscited by 63
  14. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Bindingcited by 58
  15. 2023Graph Denoising Diffusion for Inverse Protein Foldingcited by 44
  16. 2022State-specific protein-ligand complex structure prediction with a multi-scale deep generative modelcited by 35
  17. 2022E3Bind: An End-to-End Equivariant Network for Protein-Ligand Dockingcited by 35
  18. 2023AbDiffuser: Full-Atom Generation of in vitro Functioning Antibodiescited by 35
  19. 2023Trans-Dimensional Generative Modeling via Jump Diffusion Modelscited by 33
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  21. 2023Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinementcited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 10; 2025: 15; 2026: 4.

29 papers.

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  1. 2024AlphaFold Meets Flow Matching for Generating Protein Ensemblescited by 105
  2. 2024Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generationcited by 53
  3. 2024Transferable Boltzmann Generatorscited by 43
  4. 2024SemlaFlow -- Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matchingcited by 40
  5. 2025FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generationcited by 20
  6. 2025Multi-domain Distribution Learning for De Novo Drug Designcited by 15
  7. 2025Flow Matching Meets Biology and Life Science: A Surveycited by 14
  8. 2025Applications of Modular Co-Design for De Novo 3D Molecule Generationcited by 13
  9. 2025dyAb: Flow Matching for Flexible Antibody Design with AlphaFold-driven Pre-binding Antigencited by 10
  10. 2025High-order Equivariant Flow Matching for Density Functional Theory Hamiltonian Predictioncited by 10
  11. 2024Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extensioncited by 9
  12. 2024FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Predictioncited by 8
17 more
  1. 2025BoltzNCE: Learning Likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimationcited by 7
  2. 2025Compositional Flows for 3D Molecule and Synthesis Pathway Co-designcited by 6
  3. 2024EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamicscited by 5
  4. 2025Energy-Based Flow Matching for Generating 3D Molecular Structurecited by 4
  5. 2025Flow Autoencoders are Effective Protein Tokenizerscited by 4
  6. 2025SigmaDock: Untwisting Molecular Docking With Fragment-Based SE(3) Diffusioncited by 3
  7. 20263D Molecule Generation from Rigid Motifs via SE(3) Flowscited by 3
  8. 2026Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materialscited by 3
  9. 2026Fast Organic Crystal Structure Prediction with Unit Cell Flow Matchingcited by 3
  10. 2025Path Gradients after Flow Matchingcited by 2
  11. 2025Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimizationcited by 2
  12. 2024Efficient Antibody Structure Refinement Using Energy-Guided SE(3) Flow Matchingcited by 1
  13. 2024PROflow: An iterative refinement model for PROTAC-induced structure predictioncited by 0
  14. 2024Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matchingcited by 0
  15. 2025polyGen: A Learning Framework for Atomic-level Polymer Structure Generationcited by 0
  16. 2025Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discoverycited by 0
  17. 2026Contrastive-Augmented Flow Matching for Style-Content Disentanglementcited by 0

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  1. 2025Prior-Guided Flow Matching for Target-Aware Molecule Design with Learnable Atom Number
  2. 2025FLOWR.root: A flow matching based foundation model for joint multi-purpose structure-aware 3D ligand generation and affinity prediction
  3. 2025FLOWR: Flow Matching for Structure-Aware De Novo, Interaction- and Fragment-Based Ligand Generation
  4. 2025Matcha: Multi-Stage Riemannian Flow Matching for Accurate and Physically Valid Molecular Docking
  5. 2026Emyx: Fast and efficient all-atom protein generation
  6. 2025THFlow: A Temporally Hierarchical Flow Matching Framework for 3D Peptide Design
  7. 2024Full-Atom Peptide Design based on Multi-modal Flow Matching
  8. 2025FlexiFlow: decomposable flow matching for generation of flexible molecular ensemble