mlsanityData to 7 Oct 2026

TransDiffSBDD: Causality-Aware Multi-Modal Structure-Based Drug Design

arXiv 2503.20913 ↗First posted 26 Mar 2025cs.CE cs.LGcited by 0

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

Abstract (arXiv)

Structure-based drug design (SBDD) is a critical task in drug discovery, requiring the generation of molecular information across two distinct modalities: discrete molecular graphs and continuous 3D coordinates. However, existing SBDD methods often overlook two key challenges: (1) the multi-modal nature of this task and (2) the causal relationship between these modalities, limiting their plausibility and performance. To address both challenges, we propose TransDiffSBDD, an integrated framework combining autoregressive transformers and diffusion models for SBDD. Specifically, the autoregressive transformer models discrete molecular information, while the diffusion model samples continuous distributions, effectively resolving the first challenge. To address the second challenge, we design a hybrid-modal sequence for protein-ligand complexes that explicitly respects the causality between modalities. Experiments on the CrossDocked2020 benchmark demonstrate that TransDiffSBDD outperforms existing baselines.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 39 of its 71 references that are in the map. First posted on arXiv 26 Mar 2025.

Builds on

39 of 71 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization1 Jul
  2. 2024Structure-based drug design by denoising voxel grids7 May
  3. 2024DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization7 Mar
  4. 2024DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design26 Feb
  5. 2022Structure-based Drug Design with Equivariant Diffusion Models24 Oct

Other references · 34

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2022Training language models to follow instructions with human feedbackcited by 15,712
  6. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  7. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,526
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  9. 2024Autoregressive Image Generation without Vector Quantizationcited by 644
  10. 2024Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Modelcited by 468
  11. 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 307
  12. 2017Molecular De Novo Design through Deep Reinforcement Learningcited by 264
22 more
  1. 2018Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Predictioncited by 225
  2. 2022Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pocketscited by 182
  3. 20233D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Predictioncited by 176
  4. 2022A 3D Generative Model for Structure-Based Drug Designcited by 148
  5. 2024Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformerscited by 145
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  9. 2023Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB filescited by 59
  10. 2024MolCRAFT: Structure-Based Drug Design in Continuous Parameter Spacecited by 48
  11. 2024Multimodal Latent Language Modeling with Next-Token Diffusioncited by 47
  12. 2022Reinforced Genetic Algorithm for Structure-based Drug Designcited by 46
  13. 2022Structure-based drug design with geometric deep learningcited by 40
  14. 2023Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaborationcited by 30
  15. 2023Learning Subpocket Prototypes for Generalizable Structure-based Drug Designcited by 25
  16. 2022Zero-Shot 3D Drug Design by Sketching and Generatingcited by 24
  17. 2023Searching for High-Value Molecules Using Reinforcement Learning and Transformerscited by 18
  18. 2023Generation of 3D Molecules in Pockets via Language Modelcited by 13
  19. 2024BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learningcited by 12
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  21. 2024Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?cited by 7
  22. 20253DMolFormer: A Dual-channel Framework for Structure-based Drug Discoverycited by 4

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