mlsanityData to 7 Oct 2026

Structure-based drug design with geometric deep learning

arXiv 2210.11250 ↗First posted 19 Oct 2022physics.chem-ph cs.LGcited by 40

Not on the map. Why?

Abstract (arXiv)

Structure-based drug design uses three-dimensional geometric information of macromolecules, such as proteins or nucleic acids, to identify suitable ligands. Geometric deep learning, an emerging concept of neural-network-based machine learning, has been applied to macromolecular structures. This review provides an overview of the recent applications of geometric deep learning in bioorganic and medicinal chemistry, highlighting its potential for structure-based drug discovery and design. Emphasis is placed on molecular property prediction, ligand binding site and pose prediction, and structure-based de novo molecular design. The current challenges and opportunities are highlighted, and a forecast of the future of geometric deep learning for drug discovery is presented.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). Builds on 24 of its 94 references that are in the map. First posted on arXiv 19 Oct 2022.

Builds on

24 of 94 references.

References · 24

  1. 2021Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gaugescited by 1,131
  2. 2016Geometric deep learning: going beyond Euclidean datacited by 1,042
  3. 2021E(n) Equivariant Graph Neural Networkscited by 951
  4. 2021E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentialscited by 701
  5. 2022Equivariant Diffusion for Molecule Generation in 3Dcited by 666
  6. 2022MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fieldscited by 467
  7. 20183D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Datacited by 348
  8. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 307
  9. 2022A 3D Generative Model for Structure-Based Drug Designcited by 148
  10. 2022EquiBind: Geometric Deep Learning for Drug Binding Structure Predictioncited by 143
  11. 2022Equivariant 3D-Conditional Diffusion Models for Molecular Linker Designcited by 121
  12. 2021Geometric Deep Learning on Molecular Representationscited by 113
12 more
  1. 2021SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effectscited by 103
  2. 2021Inverse design of 3d molecular structures with conditional generative neural networkscited by 93
  3. 2021Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Dockingcited by 81
  4. 2021SE(3)-equivariant prediction of molecular wavefunctions and electronic densitiescited by 67
  5. 2021Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinitycited by 60
  6. 2022Multi-Scale Representation Learning on Proteinscited by 52
  7. 2018PotentialNet for Molecular Property Predictioncited by 46
  8. 2021Learning to design drug-like molecules in three-dimensional space using deep generative modelscited by 37
  9. 2020PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictionscited by 31
  10. 2021Geometric Transformers for Protein Interface Contact Predictioncited by 18
  11. 2022Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulationscited by 9
  12. 2022Efficient and Accurate Physics-aware Multiplex Graph Neural Networks for 3D Small Molecules and Macromolecule Complexescited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 8; 2024: 11; 2025: 12; 2026: 9.

40 papers.

Sort:

By area:

  1. 2024MolCRAFT: Structure-Based Drug Design in Continuous Parameter Spacecited by 48
  2. 2023Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materialscited by 22
  3. 2023EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Predictioncited by 15
  4. 2024ReactZyme: A Benchmark for Enzyme-Reaction Predictioncited by 13
  5. 2023A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systemscited by 10
  6. 2023Learning Harmonic Molecular Representations on Riemannian Manifoldcited by 8
  7. 2024Empower Structure-Based Molecule Optimization with Gradient Guided Bayesian Flow Networkscited by 6
  8. 2025Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedulecited by 6
  9. 2023AtomSurf : Surface Representation for Learning on Protein Structurescited by 5
  10. 2024Effective Protein-Protein Interaction Exploration with PPIretrievalcited by 5
  11. 2024EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamicscited by 5
  12. 20253DMolFormer: A Dual-channel Framework for Structure-based Drug Discoverycited by 4
28 more
  1. 2024TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Modelscited by 3
  2. 2025UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detectioncited by 3
  3. 2023Geometric Deep Learning for Structure-Based Drug Design: A Surveycited by 2
  4. 2024BInD: Bond and Interaction-generating Diffusion Model for Multi-objective Structure-based Drug Designcited by 2
  5. 2025Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteinscited by 2
  6. 2026Speaking the Language of Science: Toward a General-Purpose Generative Foundation Model for the Natural Sciencescited by 2
  7. 2023Geometric Epitope and Paratope Predictioncited by 1
  8. 2024Dockformer: A transformer-based molecular docking paradigm for large-scale virtual screeningcited by 1
  9. 2025Molecule Generation for Target Protein Binding with Hierarchical Consistency Diffusion Modelcited by 1
  10. 2025MolPIF: A Parameter Interpolation Flow Model for Molecule Generationcited by 1
  11. 2026TSSR: Two-Stage Swap-Reward-Driven Reinforcement Learning for Character-Level SMILES Generationcited by 1
  12. 2023MoleCLUEs: Molecular Conformers Maximally In-Distribution for Predictive Modelscited by 0
  13. 2024Quantum-Inspired Machine Learning for Molecular Dockingcited by 0
  14. 2024CADReN: Contextual Anchor-Driven Relational Network for Controllable Cross-Graphs Node Importance Estimationcited by 0
  15. 2024CW-CNN & CW-AN: Convolutional Networks and Attention Networks for CW-Complexescited by 0
  16. 2025Concept-Driven Deep Learning for Enhanced Protein-Specific Molecular Generationcited by 0
  17. 2025TransDiffSBDD: Causality-Aware Multi-Modal Structure-Based Drug Designcited by 0
  18. 2025MSCoD: An Enhanced Bayesian Updating Framework with Multi-Scale Information Bottleneck and Cooperative Attention for Structure-Based Drug Designcited by 0
  19. 2025HyperDiffusionFields (HyDiF): Diffusion-Guided Hypernetworks for Learning Implicit Molecular Neural Fieldscited by 0
  20. 2025SHA-256 Infused Embedding-Driven Generative Modeling of High-Energy Molecules in Low-Data Regimescited by 0
  21. 2025SculptDrug : A Spatial Condition-Aware Bayesian Flow Model for Structure-based Drug Designcited by 0
  22. 2026EvoEGF-Mol: Evolving Exponential Geodesic Flow for Structure-based Drug Designcited by 0
  23. 2026Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Designcited by 0
  24. 2026Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimizationcited by 0
  25. 2026Probe Before You Edit: Probing-Guided Molecular Optimization for LLM Agents in Structure-Based Drug Designcited by 0
  26. 2026A Complexity Measure for Active Learning in Multi-group Mean Estimationcited by 0
  27. 2026PocketVE: Stable and Property-Guided Structure-Based Drug Design with Variance-Exploding Diffusioncited by 0
  28. 2026A Systematic Evaluation of Molecule Generation Models for De Novo Drug Design: From Benchmarks to Practical Insightscited by 0