mlsanityData to 7 Oct 2026

3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction

arXiv 2303.03543 ↗First posted 6 Mar 2023q-bio.BM cs.LGcited by 176

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Cited by 70 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Rich data and powerful machine learning models allow us to design drugs for a specific protein target textitin silico. Recently, the inclusion of 3D structures during targeted drug design shows superior performance to other target-free models as the atomic interaction in the 3D space is explicitly modeled. However, current 3D target-aware models either rely on the voxelized atom densities or the autoregressive sampling process, which are not equivariant to rotation or easily violate geometric constraints resulting in unrealistic structures. In this work, we develop a 3D equivariant diffusion model to solve the above challenges. To achieve target-aware molecule design, our method learns a joint generative process of both continuous atom coordinates and categorical atom types with a SE(3)-equivariant network. Moreover, we show that our model can serve as an unsupervised feature extractor to estimate the binding affinity under proper parameterization, which provides an effective way for drug screening. To evaluate our model, we propose a comprehensive framework to evaluate the quality of sampled molecules from different dimensions. Empirical studies show our model could generate molecules with more realistic 3D structures and better affinities towards the protein targets, and improve binding affinity ranking and prediction without retraining.

Key facts. Cited by 176 papers in the map (data through 7 Oct 2026). Builds on 37 of its 68 references that are in the map. First posted on arXiv 6 Mar 2023.

Builds on

37 of 68 references.

References · 37

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  4. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  5. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  6. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,665
  7. 2021E(n) Equivariant Graph Neural Networkscited by 951
  8. 2016Automatic chemical design using a data-driven continuous representation of moleculescited by 762
  9. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 735
  10. 2022Equivariant Diffusion for Molecule Generation in 3Dcited by 666
  11. 2018Junction Tree Variational Autoencoder for Molecular Graph Generationcited by 647
  12. 2020SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networkscited by 602
25 more
  1. 2021Argmax Flows and Multinomial Diffusion: Learning Categorical Distributionscited by 566
  2. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generationcited by 511
  3. 2018Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generationcited by 363
  4. 2020GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generationcited by 301
  5. 2017Grammar Variational Autoencodercited by 283
  6. 2020Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densitiescited by 248
  7. 2018Learning Deep Generative Models of Graphscited by 227
  8. 2018Optimization of Molecules via Deep Reinforcement Learningcited by 199
  9. 2018Constrained Graph Variational Autoencoders for Molecule Designcited by 182
  10. 2022Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pocketscited by 182
  11. 2019Symmetry-adapted generation of 3d point sets for the targeted discovery of moleculescited by 171
  12. 2021E(n) Equivariant Normalizing Flowscited by 165
  13. 2022A 3D Generative Model for Structure-Based Drug Designcited by 148
  14. 2022EquiBind: Geometric Deep Learning for Drug Binding Structure Predictioncited by 143
  15. 2022Generating 3D Molecules for Target Protein Bindingcited by 104
  16. 2021Generating 3D Molecules Conditional on Receptor Binding Sites with Deep Generative Modelscited by 72
  17. 2020Symmetry-Aware Actor-Critic for 3D Molecular Designcited by 55
  18. 2022Multi-Scale Representation Learning on Proteinscited by 52
  19. 2020Reinforcement Learning for Molecular Design Guided by Quantum Mechanicscited by 51
  20. 2021Learning to design drug-like molecules in three-dimensional space using deep generative modelscited by 37
  21. 2017Molecular Generation with Recurrent Neural Networks (RNNs)cited by 36
  22. 2020A Deep Generative Model for Fragment-Based Molecule Generationcited by 24
  23. 2020Learning a Continuous Representation of 3D Molecular Structures with Deep Generative Modelscited by 24
  24. 2022Target-aware Molecular Graph Generationcited by 18
  25. 2020Multi-Objective Molecule Generation using Interpretable Substructurescited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 16; 2024: 55; 2025: 58; 2026: 47.

176 papers.

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  1. 2024DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Designcited by 87
  2. 2025Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Expertscited by 85
  3. 2024EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learningcited by 72
  4. 2023MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generationcited by 65
  5. 2024Equivariant Diffusion Policycited by 61
  6. 2023On the Design Fundamentals of Diffusion Models: A Surveycited by 59
  7. 2023CoCoGen: Physically-Consistent and Conditioned Score-based Generative Models for Forward and Inverse Problemscited by 54
  8. 2024Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generationcited by 53
  9. 2023Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generationcited by 50
  10. 2024MolCRAFT: Structure-Based Drug Design in Continuous Parameter Spacecited by 48
  11. 2024SemlaFlow -- Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matchingcited by 40
  12. 20233D molecule generation by denoising voxel gridscited by 38
38 more
  1. 2023Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaborationcited by 30
  2. 2024A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generationcited by 29
  3. 2024A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applicationscited by 28
  4. 2024DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimizationcited by 27
  5. 2024Flow matching achieves almost minimax optimal convergencecited by 27
  6. 2024PPFlow: Target-aware Peptide Design with Torsional Flow Matchingcited by 26
  7. 2024Diffusion Models in textitDe Novo Drug Designcited by 26
  8. 2024Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimizationcited by 25
  9. 2024ET-SEED: Efficient Trajectory-Level SE(3) Equivariant Diffusion Policycited by 24
  10. 2025LIDDIA: Language-based Intelligent Drug Discovery Agentcited by 24
  11. 2024Generative Flows on Synthetic Pathway for Drug Designcited by 20
  12. 2024UniGEM: A Unified Approach to Generation and Property Prediction for Moleculescited by 20
  13. 2025PharmAgents: Building a Virtual Pharma with Large Language Model Agentscited by 20
  14. 2025FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generationcited by 20
  15. 2024CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graphcited by 19
  16. 2024Structure-based drug design by denoising voxel gridscited by 18
  17. 2025FLOWR: Flow Matching for Structure-Aware De Novo, Interaction- and Fragment-Based Ligand Generationcited by 18
  18. 2023Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modelingcited by 17
  19. 2025RNE: plug-and-play diffusion inference-time control and energy-based trainingcited by 16
  20. 2025Multi-domain Distribution Learning for De Novo Drug Designcited by 15
  21. 2024Zero-Shot Uncertainty Quantification using Diffusion Probabilistic Modelscited by 14
  22. 2023Generation of 3D Molecules in Pockets via Language Modelcited by 13
  23. 2024Geometric Trajectory Diffusion Modelscited by 13
  24. 2024Binding-Adaptive Diffusion Models for Structure-Based Drug Designcited by 12
  25. 2024TAGMol: Target-Aware Gradient-guided Molecule Generationcited by 12
  26. 2024BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learningcited by 12
  27. 2023Distilling ODE Solvers of Diffusion Models into Smaller Stepscited by 11
  28. 2024Text-guided multi-property molecular optimization with a diffusion language modelcited by 11
  29. 2024Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Designcited by 11
  30. 2024Exploring Discrete Flow Matching for 3D De Novo Molecule Generationcited by 11
  31. 2025UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Designcited by 11
  32. 2024Advancing biomolecular understanding and design following human instructionscited by 10
  33. 2025Generating 3D Binding Molecules Using Shape-Conditioned Diffusion Models with Guidancecited by 10
  34. 2024Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusioncited by 9
  35. 2025SynLlama: Generating Synthesizable Molecules and Their Analogs with Large Language Modelscited by 9
  36. 2024Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Processcited by 8
  37. 2023CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer Generationcited by 7
  38. 2023Shape-conditioned 3D Molecule Generation via Equivariant Diffusion Modelscited by 7

50 most cited of 176 All 176 (JSON)

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  1. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
  2. 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design
  3. 2024PILOT: Equivariant diffusion for pocket conditioned de novo ligand generation with multi-objective guidance via importance sampling
  4. 2025D3MES: Diffusion Transformer with multihead equivariant self-attention for 3D molecule generation
  5. 2024Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation
  6. 2022Structure-based Drug Design with Equivariant Diffusion Models
  7. 2024ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
  8. 2025Frame-based Equivariant Diffusion Models for 3D Molecular Generation