Molecular design

related to **Generative AI** and **Deep Learning** for **molecular/drug design** and **molecular conformation generation**.
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Molecular Optimization
Molecular Optimization will welcome ！！！
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**Molecular(drug) Design Using Generative Artificial Intelligence and Deep Learning**
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| Unified Deep Molecular Generative Model | | | |
| Generative AI for Scientific Discovery | Reviews | Datasets and Benchmarks | Drug-likeness and Evaluation metrics |
| Deep Learning-based design | Text-driven molecular generation models | Multi-Target based deep molecular generative models | Ligand-based deep molecular generative models |
| Pharmacophore-based deep molecular generative models | Structure-based deep molecular generative models | Fragment-based deep molecular generative models | Scaffold-based DMGs |
| Fragment-based DMGs | Motifs-based DMGs | Linkers-based DMGs | Chemical Reaction-based deep molecular generative models |
| Omics-based deep molecular generative models | Multi-Objective deep molecular generative models | Quantum deep molecular generative models | Recommendations and References |
| Spectra(Mass/NMR)-based | Mass Spectra-based | NMR Spectra-based | Cryo-EM Maps-based |
- Drug-likeness and Evaluation metrics
| Datasets | Benchmarks | Drug-likeness| Evaluation metrics |
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| Datasets | Benchmarks | QED | SAscore |
| | | QEPPI | RAscore |
| | | | Evaluation metrics |
| | | | Molecular generative validation |
- Generative AI for Molecular Conformation
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| Benchmark for Molecular Conformer Ensembles | Reviews for Molecular Conformation Generation |
| VAE-based Molecular Conformation Generation | GAN-based Molecular Conformation Generation |
| Energy-based Molecular Conformation Generation | Flow Matching-based Molecular Conformation Generation |
| Diffusion-based Molecular Conformation Generation | |
| RL-based Molecular Conformation Generation | |
| GNN-based Molecular Conformation Generation | |
- Deep Learning-based drug design
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| RNN-based | LSTM-based | Autoregressive-models | Transformer-based |
| VAE-based | GAN-based | Flow-based | Flow matching-based |
| Prompt-based | Score-Based | Energy-based | Diffusion-based |
| Active Learning DMGs | RL-based | Multi-task DMGs | Tree Search |
| Genetic Algorithm-based | Evolutionary Algorithm-based | Large Language Model-based | Agent-based |
**Material Design Using Generative Artificial Intelligence and Deep Learning**
- Deep Learning-based material design
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Recommendations and References
**awesome-AI4ProteinConformation-MD**
https://github.com/AspirinCode/awesome-AI4ProteinConformation-MD
**Large Language Model for Biomedical Science, Molecule, Protein, Material Discovery**
https://github.com/HHW-zhou/LLM4Mol
**List of papers about Proteins Design using Deep Learning**
https://github.com/Peldom/papers_for_protein_design_using_DL
**Awesome Generative AI**
https://github.com/steven2358/awesome-generative-ai
**awesome-molecular-generation**
https://github.com/amorehead/awesome-molecular-generation
**A Survey of Artificial Intelligence in Drug Discovery**
https://github.com/dengjianyuan/Survey_AI_Drug_Discovery
**Geometry Deep Learning for Drug Discovery and Life Science**
https://github.com/3146830058/Geometry-Deep-Learning-for-Drug-Discovery-and-Life-Science
Unified Deep Molecular Generative Model
* **All-atom Diffusion Transformers: Unified generative modelling of molecules and materials** [2025]
Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao, Vahe Gharakhanyan, Benjamin Kurt Miller, Anuroop Sriram, Zachary W. Ulissi.
arXiv:2503.03965 (2025)
* **UniGenX: Unified Generation of Sequence and Structure with Autoregressive Diffusion** [2025]
Zhang, Gongbo, Yanting Li, Renqian Luo, Pipi Hu, Zeru Zhao, Lingbo Li, Guoqing Liu et al.
arXiv:2503.06687 (2025)
Generative AI for Scientific Discovery
* **Accelerating Material Design with the Generative Toolkit for Scientific Discovery**
Manica, Matteo and Cadow, Joris and Christofidellis, Dimitrios and Dave, Ashish and Born, Jannis and Clarke, Dean and Teukam, Yves Gaetan Nana and Hoffman, Samuel C and Buchan, Matthew and Chenthamarakshan, Vijil and others
npj Comput Mater 9, 69 (2023) | code
Reviews
* **From Computational Chemistry to Generative Models: A Survey of AI-Driven Small-Molecule Drug Discovery** [2026]
Houman Kazemzadeh, Kiarash Mokhtari, Nazanin Mirzaei, et al.
ChemRxiv. (2026)
* **How Molecular Generative Models Organize Molecular Identity** [2026]
Raul Ortega-Ochoa, Tejs Vegge, Jens S. Bakander, Luis Mantilla Calderon, Alan Aspuru-Guzik, Tonio Buonassisi.
arXiv:2608.06956(2026)
* **A comprehensive review of artificial intelligence in drug design: methods, applications, and challenges** [2026]
Fang, Yi, Xiaoyong Pan, and Hong-Bin Shen.
Digital Discovery (2026)
* **Structure-Based Drug Design with Geometric Deep Learning: A Comprehensive Survey** [2025]