Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery

Cited by (279)

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    Yang Liao, Zhangle Wei, Hangwei Xu, Zhichao Zhang, Feng Zhu · 2024 · Precision medication.
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  23. Saccharide concentration prediction from proxy-sea surface microlayer samples analyzed via ATR-FTIR spectroscopy and quantitative machine learning
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  25. THE AI REVOLUTION IN PHARMACEUTICALS: INNOVATIONS, CHALLENGES, AND FUTURE PROSPECTS – AN OVERVIEW
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  26. Defining chemical problems for artificial intelligence models
    Joonyoung F. Joung · 2026 · Bulletin of the Korean Chemical Society
  27. De Novo Drug Design via Multi-Label Learning and Adversarial Autoencoder
    Qing Ye, Xiaolong Zhang, Xiaoli Lin · 2021 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  28. Status and Prospects of Research on Deep Learning-based De Novo Generation of Drug Molecules
    Huanghao Shi, Zhichao Wang, Litao Zhou, Zhiwang Xu, Liangxu Xie, Ren Kong, Shan Chang · 2024 · Current Computer - Aided Drug Design
  29. Drug Molecule Generation Method Based on Fusion of Protein Sequence Features
    Mengyao Wang, Xiaolong Zhang, Haoran Liu, Xiaoli Lin, Jing Hu, Jun Pang · 2024 · Lecture notes in computer science
  30. A generative neural network based on a hetero-encoder model for de novo design of potential anticancer drugs: application to Bcr-Abl tyrosine kinase
    Anna D. Karpenko, T. D. Vaitko, Alexander V. Tuzikov, Alexander M. Andrianov · 2023 · Informatics
  31. Application of transformer model architecture in the new drugs design
    Давронов Рифкат Раxимович, Abdumalikov Shoxrux Qaxramon O'g'li, Safarov Ro'zmat Abdiqayum O'g'li · 2021 · International Conference on Information Science and Communications Technologies (ICISCT)
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  48. Deep learning methodologies in drug design
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    Xiaohan Lin, Yijie Xia, Yupeng Huang, Shuo Liu, Jun Zhang, Yi Qin Gao · 2024 · ChemRxiv
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  55. ADMETrix: ADMET-Driven De Novo Molecular Generation
    Nikolaos Mourdoukoutas, Aigli Korfiati, Vasilis Pitsikalis · 2025 · ChemRxiv
  56. ADMETrix: ADMET-Driven De Novo Molecular Generation
    Nikolaos Mourdoukoutas, Aigli Korfiati, Vasilis Pitsikalis · 2025 · ChemRxiv
  57. Intelligent design and synthesis of nucleobase and amino acid-based ligands to inhibit the JAK2 enzyme to treat rheumatoid arthritis
    Ameneh Zarei, Alireza Fattahi · 2025 · Amino Acids
  58. Additional file 1 of CReM: chemically reasonable mutations framework for structure generation
    Павел Геннадьевич Полищук · 2020 · Figshare
  59. Additional file 1 of MolFilterGAN: a progressively augmented generative adversarial network for triaging AI-designed molecules
    Liu, Xiaohong, Zhang, Wei, Tong, Xiaochu, Feisheng Zhong, Li, Zhaojun, Zhaoping Xiong, Jiacheng Xiong, Wu, Xiaolong, Zunyun Fu, Tan, Xiaoqin et al. · 2024 · Figshare
  60. AgainstOTE: A generative pretrain-tune framework for de novo molecular generation against off-target effects
    Yechao Xu, Wen Fang, Shuai Wang, Hai-Bin Luo, Qiang Xu, Fen-Er Chen, Jiao Qu, Yang Sun · 2025 · The Innovation Medicine
  61. Molecule Generation Models
    ShuiGeng ZHOU · 2025 · Springer eBooks
  62. From Latent Manifolds to Targeted Molecular Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework for Family-Based Kinase Ligand Design
    Gennady M. Verkhivker, Ryan Kassab, Keerthi Krishnan · 2026 · Biomolecules
  63. Network-based machine learning methods to model variability across individuals
    Behnam Yousefi · 2023 · theses.fr (ABES)
  64. Revolutionizing Drug Discovery: The Evolving Role of Artificial Intelligence and Machine Learning
    Harikrishna Bommala · 2026 · International Journal of Creative and Open Research in Engineering and Management
  65. CReM update: a faster, more compact, and more flexible framework for chemically reasonable mutations
    Павел Геннадьевич Полищук · 2026 · ChemRxiv
  66. Machine Learning in Natural Product-based Drug Discovery
    Gargee Mahajan, Neha Kadam, Prashant S. Kharkar · 2026 · Royal Society of Chemistry eBooks
  67. Chemical Language Model Applications in Medicinal Chemistry
    Gauri Mishra, Vaibhav A. Dixit · 2026 · Royal Society of Chemistry eBooks
  68. GANs in Peptide Drug Discovery: From De Novo Design to Multi-Property Optimization and Clinical Translation
    Yanyan Chu, Shanshan Zhang, Bin Pan, Qingbao Zhang, Xin Zhou, Ying Liu, Feng Li · 2026 · Probiotics and Antimicrobial Proteins
  69. From Computational Chemistry to Generative Models: A Survey of AI-Driven Small-Molecule Drug Discovery
    Houman Kazemzadeh, Kiarash Mokhtari, Nazanin Mirzaei, Seyed Reza Tavakoli, Ali Reza Keivanimehr, Shayan Majidifar, Ali Behrad, Farbod Davoodi, Sina Khosravi, Behdad Alikhani et al. · 2026 · ChemRxiv
  70. From Computational Chemistry to Generative Models: A Survey of AI-Driven Small-Molecule Drug Discovery
    Houman Kazemzadeh, Kiarash Mokhtari, Seyed Reza Tavakoli, Nazanin Mirzaei, Ali Reza Keivanimehr, Shayan Majidifar, Ali Behrad, Farbod Davoodi, Sina Khosravi, Behdad Alikhani et al. · 2026 · ChemRxiv
  71. Revolutionizing Pharmaceuticals With AI-Driven Drug Delivery, Design, and Development
    K. Kesavardhini, P. Saranraj, Balachander Lokeshwari, Krishnaswamy Veena Gayathri, K. Arthi · 2026 · Advances in computational intelligence and robotics book series
  72. BindingDB Entry 50010960: Learning Molecular Representations for Medicinal Chemistry.
    BindingDB · 2021 · UC San Diego
  73. BindingDB Entry 50023694: Design, Synthesis, and Biological Evaluation of Novel Orally Available Covalent CDK12/13 Dual Inhibitors for the Treatment of Tumors.
    BindingDB · 2026 · UC San Diego
  74. BindingDB Entry 50020701: Discovery of Potent, Selective, and Orally Bioavailable Small-Molecule Inhibitors of CDK8 for the Treatment of Cancer.
    BindingDB · 2024 · UC San Diego
  75. BindingDB Entry 50023008: Discovery of a Novel Macrocyclic Noncovalent CDK7 Inhibitor for Cancer Therapy.
    BindingDB · 2026 · UC San Diego
  76. BindingDB Entry 50022937: Discovery of Potent, Highly Selective, and Orally Bioavailable MTA Cooperative PRMT5 Inhibitors with Robust In Vivo Antitumor Activity.
    BindingDB · 2026 · UC San Diego
  77. BindingDB Entry 50021522: Discovery of Tetrahydropyrazolopyrazine Derivatives as Potent and Selective MYT1 Inhibitors for the Treatment of Cancer.
    BindingDB · 2025 · UC San Diego
  78. BindingDB Entry 50021620: Discovery of Novel and Potent Prolyl Hydroxylase Domain-Containing Protein (PHD) Inhibitors for The Treatment of Anemia.
    BindingDB · 2025 · UC San Diego
  79. A BRAF-focused computational pipeline integrating GPT-based molecular generation, hybrid-reward reinforcement learning and retrosynthetic prioritization
    Nikoletta-Maria Koutroumpa, Konstantinos D. Papavasileiou, Haralambos Tzoupis, Charis Georgiou, Alexios N. Matralis, Georgia Melagraki, Antreas Afantitis · 2026 · Artificial Intelligence Chemistry