mlsanityData to 7 Oct 2026

Diffusion Models in textitDe Novo Drug Design

arXiv 2406.08511 ↗First posted 7 Jun 2024physics.chem-ph cs.LGcited by 26

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

Abstract (arXiv)

Diffusion models have emerged as powerful tools for molecular generation, particularly in the context of 3D molecular structures. Inspired by non-equilibrium statistical physics, these models can generate 3D molecular structures with specific properties or requirements crucial to drug discovery. Diffusion models were particularly successful at learning 3D molecular geometries' complex probability distributions and their corresponding chemical and physical properties through forward and reverse diffusion processes. This review focuses on the technical implementation of diffusion models tailored for 3D molecular generation. It compares the performance, evaluation methods, and implementation details of various diffusion models used for molecular generation tasks. We cover strategies for atom and bond representation, architectures of reverse diffusion denoising networks, and challenges associated with generating stable 3D molecular structures. This review also explores the applications of diffusion models in textitde novo drug design and related areas of computational chemistry, such as structure-based drug design, including target-specific molecular generation, molecular docking, and molecular dynamics of protein-ligand complexes. We also cover conditional generation on physical properties, conformation generation, and fragment-based drug design. By summarizing the state-of-the-art diffusion models for 3D molecular generation, this review sheds light on their role in advancing drug discovery as well as their current limitations.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 79 of its 136 references that are in the map. First posted on arXiv 7 Jun 2024.

Builds on

79 of 136 references.

Closest ancestors · 20

Same direction, newest first

  1. 2024DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization7 Mar
  2. 2024DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design26 Feb
  3. 2024Binding-Adaptive Diffusion Models for Structure-Based Drug Design15 Jan
  4. 2024Geometric-Facilitated Denoising Diffusion Model for 3D Molecule Generation5 Jan
  5. 2023Autoregressive fragment-based diffusion for pocket-aware ligand design15 Dec
  6. 2023Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation21 May
  7. 2023Geometric Latent Diffusion Models for 3D Molecule Generation2 May
  8. 2023SILVR: Guided Diffusion for Molecule Generation21 Apr
  9. 2023A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material4 Apr
  10. 2023Geometry-Complete Diffusion for 3D Molecule Generation and Optimization8 Feb
  11. 2023Generative Diffusion Models on Graphs: Methods and Applications6 Feb
  12. 2023Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics1 Feb
8 more
  1. 2022Fast Graph Generation via Spectral Diffusion16 Nov
  2. 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design11 Oct
  3. 2022Diffusion Models for Graphs Benefit From Discrete State Spaces4 Oct
  4. 2022MDM: Molecular Diffusion Model for 3D Molecule Generation13 Sep
  5. 2022DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations19 Apr
  6. 2022Equivariant Diffusion for Molecule Generation in 3D31 Mar
  7. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation6 Mar
  8. 2022Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations5 Feb

Other references · 59

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2020Denoising Diffusion Implicit Modelscited by 9,655
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  6. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  7. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  8. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  9. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  10. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 2,994
  11. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,286
  12. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,961
38 more
  1. 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,571
  2. 2021Variational Diffusion Modelscited by 1,145
  3. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  4. 2019Strategies for Pre-training Graph Neural Networkscited by 964
  5. 2020A Generalization of Transformer Networks to Graphscited by 653
  6. 2017SchNet: A continuous-filter convolutional neural network for modeling quantum interactionscited by 569
  7. 2015An Introduction to Convolutional Neural Networkscited by 510
  8. 2020Principal Neighbourhood Aggregation for Graph Netscited by 477
  9. 2022MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fieldscited by 467
  10. 2018MolGAN: An implicit generative model for small molecular graphscited by 392
  11. 2019Sliced Score Matching: A Scalable Approach to Density and Score Estimationcited by 381
  12. 2018GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoderscited by 375
  13. 2019Analyzing Learned Molecular Representations for Property Predictioncited by 373
  14. 2022Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioningcited by 362
  15. 2022Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Modelscited by 331
  16. 2020GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generationcited by 301
  17. 2018GuacaMol: Benchmarking Models for De Novo Molecular Designcited by 294
  18. 2018Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Modelscited by 270
  19. 2022Torsional Diffusion for Molecular Conformer Generationcited by 262
  20. 2018Learning Deep Generative Models of Graphscited by 227
  21. 2020MoFlow: An Invertible Flow Model for Generating Molecular Graphscited by 183
  22. 2018Constrained Graph Variational Autoencoders for Molecule Designcited by 182
  23. 2022Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pocketscited by 182
  24. 2021GraphDF: A Discrete Flow Model for Molecular Graph Generationcited by 177
  25. 20233D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Predictioncited by 176
  26. 2023MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adaptercited by 128
  27. 2019GraphNVP: An Invertible Flow Model for Generating Molecular Graphscited by 115
  28. 2022Diffusion-based Molecule Generation with Informative Prior Bridgescited by 104
  29. 2018Multi-Objective De Novo Drug Design with Conditional Graph Generative Modelcited by 101
  30. 2022Exploring Chemical Space with Score-based Out-of-distribution Generationcited by 95
  31. 2019MolecularRNN: Generating realistic molecular graphs with optimized propertiescited by 80
  32. 2022SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentialscited by 80
  33. 2022Equivariant Energy-Guided SDE for Inverse Molecular Designcited by 72
  34. 2018NeVAE: A Deep Generative Model for Molecular Graphscited by 66
  35. 2023MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generationcited by 65
  36. 2022DiffBP: Generative Diffusion of 3D Molecules for Target Protein Bindingcited by 58
  37. 2019Neural Empirical Bayescited by 46
  38. 2023Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generationcited by 46

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 15; 2026: 8.

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  1. 2024An analytic theory of creativity in convolutional diffusion modelscited by 103
  2. 2024How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Frameworkcited by 48
  3. 2025Bigger Isn't Always Memorizing: Early Stopping Overparameterized Diffusion Modelscited by 24
  4. 2024Understanding and Mitigating Memorization in Generative Models via Sharpness of Probability Landscapescited by 20
  5. 2025Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Modelscited by 20
  6. 2025Discrete Diffusion Models: Novel Analysis and New Sampler Guaranteescited by 20
  7. 2025Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approachcited by 18
  8. 2025Artificial Intelligence and Generative Models for Materials Discovery -- A Reviewcited by 8
  9. 2026Sharp Convergence Rates for Masked Diffusion Modelscited by 8
  10. 2026Proteo-R1: Reasoning Foundation Models for De Novo Protein Designcited by 6
  11. 2025Sampling 3D Molecular Conformers with Diffusion Transformerscited by 5
  12. 2025ScaffoldGPT: A Scaffold-based GPT Model for Drug Optimizationcited by 3
14 more
  1. 2025Group-Equivariant Diffusion Models for Lattice Field Theorycited by 3
  2. 2025Generative Models for Crystalline Materialscited by 3
  3. 2025Pharmacophore-Conditioned Diffusion Model for Ligand-Based De Novo Drug Designcited by 2
  4. 2025RAPID-Net: Accurate Pocket Identification for Binding-Site-Agnostic Dockingcited by 1
  5. 2025READ: A Retrieval-Alignment Diffusion Framework for Structure-based Drug Designcited by 1
  6. 2026From Scores to Gibbs Correctors: Accelerating Uniform-Rate Discrete Diffusion Modelscited by 1
  7. 2026Minimax Optimality of Score-Entropy Discrete Diffusioncited by 1
  8. 2025A collaborative constrained graph diffusion model for the generation of realistic synthetic moleculescited by 0
  9. 2025Towards Photonic Band Diagram Generation with Transformer-Latent Diffusion Modelscited by 0
  10. 2025Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules versus Therapeutic Peptidescited by 0
  11. 2026Interpreting the Synchronization Gap: The Hidden Mechanism Inside Diffusion Transformerscited by 0
  12. 2026Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Designcited by 0
  13. 2026A Systematic Evaluation of Molecule Generation Models for De Novo Drug Design: From Benchmarks to Practical Insightscited by 0
  14. 2026Physics-Guided Conditional Diffusion Model for Rare Event Synthesis and Diagnosis for the Water-Gas Shift Reactioncited by 0

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  1. 2023Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
  2. 2026Breaking the Bottlenecks: Scalable Diffusion Models for 3D Molecular Generation
  3. 2025Unraveling the Potential of Diffusion Models in Small Molecule Generation
  4. 2023Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D
  5. 2025Diffusion Models for Molecules: A Survey of Methods and Tasks
  6. 2024Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation
  7. 2023Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules with Desirable Properties
  8. 2024AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design