mlsanityData to 14 Oct 2026

Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design

arXiv 2210.05274 ↗First posted 11 Oct 2022cs.LG q-bio.BMcited by 122

On the map: Diffusion models → Flow matching, time series and science

Abstract (arXiv)

Fragment-based drug discovery has been an effective paradigm in early-stage drug development. An open challenge in this area is designing linkers between disconnected molecular fragments of interest to obtain chemically-relevant candidate drug molecules. In this work, we propose DiffLinker, an E(3)-equivariant 3D-conditional diffusion model for molecular linker design. Given a set of disconnected fragments, our model places missing atoms in between and designs a molecule incorporating all the initial fragments. Unlike previous approaches that are only able to connect pairs of molecular fragments, our method can link an arbitrary number of fragments. Additionally, the model automatically determines the number of atoms in the linker and its attachment points to the input fragments. We demonstrate that DiffLinker outperforms other methods on the standard datasets generating more diverse and synthetically-accessible molecules. Besides, we experimentally test our method in real-world applications, showing that it can successfully generate valid linkers conditioned on target protein pockets.

Key facts. Cited by 122 papers in the map (data through 14 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 22 of its 95 references that are in the map. First posted on arXiv 11 Oct 2022.

Builds on

22 of 95 references.

Closest ancestors · 4

Same direction, newest first

  1. 2022DiGress: Discrete Denoising diffusion for graph generation29 Sep
  2. 2022Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem8 Jun
  3. 2022Equivariant Diffusion for Molecule Generation in 3D31 Mar
  4. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation6 Mar

Other references · 18

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  3. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  4. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,719
  5. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,430
  6. 2021Variational Diffusion Modelscited by 1,153
  7. 2016Automatic chemical design using a data-driven continuous representation of moleculescited by 765
  8. 2021Argmax Flows and Multinomial Diffusion: Learning Categorical Distributionscited by 574
  9. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 313
  10. 2022Torsional Diffusion for Molecular Conformer Generationcited by 263
  11. 2020GEOM: Energy-annotated molecular conformations for property prediction and molecular generationcited by 243
  12. 2021E(n) Equivariant Normalizing Flowscited by 165
6 more
  1. 2021Learning Gradient Fields for Molecular Conformation Generationcited by 163
  2. 2021Provably Strict Generalisation Benefit for Equivariant Modelscited by 91
  3. 2021Learning Neural Generative Dynamics for Molecular Conformation Generationcited by 88
  4. 2021An End-to-End Framework for Molecular Conformation Generation via Bilevel Programmingcited by 59
  5. 20223DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Designcited by 33
  6. 2022Improving the Sample-Complexity of Deep Classification Networks with Invariant Integrationcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 3; 2023: 28; 2024: 41; 2025: 30; 2026: 20.

122 papers.

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  1. 2022Structure-based Drug Design with Equivariant Diffusion Modelscited by 217
  2. 2023SE(3)-Stochastic Flow Matching for Protein Backbone Generationcited by 150
  3. 2024Iterated Denoising Energy Matching for Sampling from Boltzmann Densitiescited by 116
  4. 2023MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generationcited by 98
  5. 2024DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Designcited by 88
  6. 2023Generative Diffusion Models on Graphs: Methods and Applicationscited by 81
  7. 2024EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learningcited by 75
  8. 2023Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamicscited by 72
  9. 2023MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generationcited by 65
  10. 2024Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generationcited by 54
  11. 2024Feedback Efficient Online Fine-Tuning of Diffusion Modelscited by 53
  12. 2025Position: Graph Learning Will Lose Relevance Due To Poor Benchmarkscited by 53
38 more
  1. 2024Does equivariance matter at scale?cited by 52
  2. 2023Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generationcited by 50
  3. 2022Structure-based drug design with geometric deep learningcited by 40
  4. 20233D molecule generation by denoising voxel gridscited by 40
  5. 2023Interpretable Diffusion via Information Decompositioncited by 37
  6. 2023EDGI: Equivariant Diffusion for Planning with Embodied Agentscited by 36
  7. 2023RetroBridge: Modeling Retrosynthesis with Markov Bridgescited by 36
  8. 2023A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Materialcited by 35
  9. 2023Trans-Dimensional Generative Modeling via Jump Diffusion Modelscited by 35
  10. 2024A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Trainingcited by 30
  11. 2024A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applicationscited by 28
  12. 2024DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimizationcited by 27
  13. 2024SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraintscited by 26
  14. 2024Diffusion Models in textitDe Novo Drug Designcited by 26
  15. 2023Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequencescited by 23
  16. 2023End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physicscited by 22
  17. 2025Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functionalcited by 20
  18. 2024CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graphcited by 19
  19. 2023Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Actioncited by 15
  20. 2024Saturn: Sample-efficient Generative Molecular Design using Memory Manipulationcited by 15
  21. 2025Multi-domain Distribution Learning for De Novo Drug Designcited by 15
  22. 2023Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problemscited by 13
  23. 2025Equivariant Neural Diffusion for Molecule Generationcited by 13
  24. 2024Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Designcited by 11
  25. 2024Exploring Discrete Flow Matching for 3D De Novo Molecule Generationcited by 11
  26. 2023Graph Structure and Feature Extrapolation for Out-of-Distribution Generalizationcited by 10
  27. 2023A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capturecited by 10
  28. 2023DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Tracescited by 10
  29. 2024Deep Lead Optimization: Leveraging Generative AI for Structural Modificationcited by 10
  30. 2024AI-driven inverse design of materials: Past, present and futurecited by 10
  31. 2026NatureBench: Can Coding Agents Match the Published SOTA of Nature-Family Papers?cited by 10
  32. 2023SILVR: Guided Diffusion for Molecule Generationcited by 9
  33. 2023Vector Field Oriented Diffusion Model for Crystal Material Generationcited by 9
  34. 2025Unified Guidance for Geometry-Conditioned Molecular Generationcited by 9
  35. 2023RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolationcited by 7
  36. 2023Autoregressive fragment-based diffusion for pocket-aware ligand designcited by 7
  37. 2024Zero Shot Molecular Generation via Similarity Kernelscited by 6
  38. 2024SpaDiT: Diffusion Transformer for Spatial Gene Expression Prediction using scRNA-seqcited by 6

50 most cited of 122 All 122 (JSON)

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  1. 2023Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D
  2. 20233D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction
  3. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
  4. 2024Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation
  5. 2024ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
  6. 2024AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design
  7. 2024Molecular Diffusion Models with Virtual Receptors
  8. 2023Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules with Desirable Properties