List of molecular design (molecular conformation generation) using Generative AI and Deep Learning

related to Generative AI and Deep Learning for molecular/drug design and molecular conformation generation.

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Molecular Optimization

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• Drug-likeness and Evaluation metrics

• Generative AI for Molecular Conformation

• Deep Learning-based design

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

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

• Deep Lead Optimization: Leveraging Generative AI for Structural Modification [2024]
  Zhang, Odin, Haitao Lin, Hui Zhang, Huifeng Zhao, Yufei Huang, Yuansheng Huang, Dejun Jiang, Chang-yu Hsieh, Peichen Pan, and Tingjun Hou.
  arXiv:2404.19230 (2024)

• Unlocking the Potential of Generative Artificial Intelligence in Drug Discovery [2024]
  Romanelli, Virgilio, Carmen Cerchia, and Antonio Lavecchia.
  Applications of Generative AI (2024)

• Recent Advances in Automated Structure-Based De Novo Drug Design [2024]
  Bai, Qifeng, Jian Ma, and Tingyang Xu.
  J. Chem. Inf. Model. (2024)

• AI Deep Learning Generative Models for Drug Discovery [2024]
  Bai, Qifeng, Jian Ma, and Tingyang Xu.
  Applications of Generative AI. Cham: Springer International Publishing (2024)

• Deep Generative Models in De Novo Drug Molecule Generation [2024]
  Xiangru Tang, Howard Dai, Elizabeth Knight, Fang Wu, Yunyang Li, Tianxiao Li, Mark Gerstein
  arXiv:2402.08703 (2024) | code

• Deep Generative Models in De Novo Drug Molecule Generation [2023]
  Chao Pang, Jianbo Qiao, Xiangxiang Zeng, Quan Zou, and Leyi Wei*
  J. Chem. Inf. Model. (2023)

• The Hitchhiker’s Guide to Deep Learning Driven Generative Chemistry [2023]
  Yan Ivanenkov, Bogdan Zagribelnyy, Alex Malyshev, Sergei Evteev, Victor Terentiev, Petrina Kamya, Dmitry Bezrukov, Alex Aliper, Feng Ren, and Alex Zhavoronkov
  ACS Med. Chem. Lett. (2023)

• Quantum computing for near-term applications in generative chemistry and drug discovery [2023]
  Pyrkov, Alexey, Alex Aliper, Dmitry Bezrukov, Yen-Chu Lin, Daniil Polykovskiy, Petrina Kamya, Feng Ren, and Alex Zhavoronkov.
  Drug Discovery Today (2023)

• A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design[2023]
  Zaixi Zhang, Jiaxian Yan, Qi Liu, Enhong Chen
  arXiv:2306.11768v2

• How will generative AI disrupt data science in drug discovery?[2023]
  Vert, JP.
  Nat Biotechnol (2023)

• Generative Models as an Emerging Paradigm in the Chemical Sciences[2023]
  Anstine, Dylan M., and Olexandr Isayev.
  JACS (2023)

• Chemical language models for de novo drug design: Challenges and opportunities[2023]
  Grisoni, Francesca.
  Current Opinion in Structural Biology 79 (2023)

• Artificial intelligence in multi-objective drug design[2023]
  Luukkonen, Sohvi, Helle W. van den Maagdenberg, Michael TM Emmerich, and Gerard JP van Westen.
  Current Opinion in Structural Biology 79 (2023)

• Integrating structure-based approaches in generative molecular design[2023]
  Thomas, Morgan, Andreas Bender, and Chris de Graaf.
  Current Opinion in Structural Biology 79 (2023)

• Open data and algorithms for open science in AI-driven molecular informatics[2023]
  Brinkhaus, Henning Otto, Kohulan Rajan, Jonas Schaub, Achim Zielesny, and Christoph Steinbeck.
  Current Opinion in Structural Biology 79 (2023)

• Structure-based drug design with geometric deep learning[2023]
  Isert, Clemens, Kenneth Atz, and Gisbert Schneider.
  Current Opinion in Structural Biology 79 (2023)

• MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design[2022]
  Du, Yuanqi, Tianfan Fu, Jimeng Sun, and Shengchao Liu.
  arXiv:2203.14500 (2022)

• Deep generative molecular design reshapes drug discovery[2022]
  Zeng, Xiangxiang, Fei Wang, Yuan Luo, Seung-gu Kang, Jian Tang, Felice C. Lightstone, Evandro F. Fang, Wendy Cornell, Ruth Nussinov, and Feixiong Cheng.
  Cell Reports Medicine (2022)

• Structure-based drug discovery with deep learning[2022]
  Özçelik, Rıza, Derek van Tilborg, José Jiménez-Luna, and Francesca Grisoni.
  ChemBioChem (2022)

• Generative models for molecular discovery: Recent advances and challenges[2022]
  Bilodeau, Camille, Wengong Jin, Tommi Jaakkola, Regina Barzilay, and Klavs F. Jensen.
  Computational Molecular Science 12.5 (2022)

• Assessing Deep Generative Models in Chemical Composition Space[2022]
  Türk, Hanna, Elisabetta Landini, Christian Kunkel, Johannes T. Margraf, and Karsten Reuter.
  Chemistry of Materials 34.21 (2022)

• Generative machine learning for de novo drug discovery: A systematic review[2022]
  Martinelli, Dominic.
  Computers in Biology and Medicine 145 (2022)

• Docking-based generative approaches in the search for new drug candidates[2022]
  Danel, Tomasz, Jan Łęski, Sabina Podlewska, and Igor T. Podolak.
  Drug Discovery Today (2022)

• Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models[2022]
  Xie, Weixin, Fanhao Wang, Yibo Li, Luhua Lai, and Jianfeng Pei.
  J. Chem. Inf. Model. 2022, 62, 10, 2269–2279

• Deep learning to catalyze inverse molecular design[2022]
  Alshehri, Abdulelah S., and Fengqi You.
  Chemical Engineering Journal 444 (2022)

• AI in 3D compound design[2022]
  Hadfield, Thomas E., and Charlotte M. Deane.
  Current Opinion in Structural Biology 73 (2022)

• Deep learning approaches for de novo drug design: An overview[2021]
  Wang, Mingyang, Zhe Wang, Huiyong Sun, Jike Wang, Chao Shen, Gaoqi Weng, Xin Chai, Honglin Li, Dongsheng Cao, and Tingjun Hou.
  Current Opinion in Structural Biology 72 (2022)

• Generative chemistry: drug discovery with deep learning generative models[2021]
  Bian, Yuemin, and Xiang-Qun Xie.
  Journal of Molecular Modeling 27 (2021)

• Generative Deep Learning for Targeted Compound Design[2021]
  Sousa, Tiago, João Correia, Vítor Pereira, and Miguel Rocha.
  J. Chem. Inf. Model. 2021, 61, 11, 5343–5361

• Generative Models for De Novo Drug Design[2021]
  Tong, Xiaochu, Xiaohong Liu, Xiaoqin