Drug Discovery

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Overview

Drug discovery aims to find and develop molecules that act on disease-relevant targets or biological processes, while balancing efficacy, safety, and the ability to make them. AI methods include graph and 3D models for predicting molecular properties, binding, and toxicity; generative models for proposing or editing molecules; and knowledge graphs and omics models for prioritizing targets and interpreting biological responses. Search and design methods increasingly combine these predictions with docking, synthesis constraints, experimental data, and tools coordinated by AI agents. A central challenge is that strong results on standard benchmarks may not transfer to unseen targets, chemistry, or assays, and computational scores still need reliable experimental validation.

Latest papers

CardsList

164 papers23 papers in the last four weeks, up 156% on the four weeks before. 0.1% of all new papers.

  1. UniD3^3: A Knowledge Graph-Enhanced RAG Framework for Drug-Disease Discovery and Reasoning

    May 31, 2026Qing Wang, Tianshi Liu, Minghao Zhou +5Relation ExtractionKG Construction

    Department of Health Outcomes and Biomedical Informatics, University of Florida, Florida, USA · Department of Hematology, H. Lee Moffitt Cancer Center and Research Institute, Florida, USA · Center for Bioinformatics and Computational Biology, Houston Methodist Research Institute, Houston, TX, USA +2

  2. A Triple-Modal Contrastive Learning Framework with Sequence, Graph, and 3D Features for Drug-Target Interaction Prediction

    May 28, 2026Le Xu, Xi Zhang, Dan Luo +2Multimodal Contrastive LearningMolecular Representation Learning

    School of Computer Science, Xiangtan University, Xiangtan 411105, China

  3. PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion

    May 27, 2026Łukasz Janisiów, Sebastian Musiał, Bartosz Zieliński +2Molecular OptimizationClassifier-Free Guidance

    Faculty of Mathematics and Computer Science, Jagiellonian University · Doctoral School of Exact and Natural Sciences, Jagiellonian University · Jagiellonian Center for Artificial Intelligence, Jagiellonian University +2

  4. Co-folding model guided by structural proteomics

    May 25, 2026Alon Shtrikman, Nitzan Simchi, Michal Ran Shchory +3Diffusion Model GuidanceProtein Structure Prediction

    1Protai Bio

  5. Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models

    May 25, 2026Qingyuan Zeng, Pengxiang Cai, Zixin Guan +5Molecular OptimizationMolecular Generation

    The Hong Kong University of Science and Technology (Guangzhou) · Guangzhou University of Chinese Medicine

  6. LipoAgent: Coordinating Fine-Tuned LLM Agents for Safer Lipid Design

    May 24, 2026Leshu Li, An Lu, Haiyu Wang +5Multi-Agent LLM SystemsMaterials Science

    New York University, USA · University of Illinois Chicago, USA

  7. An accurate nucleic acid-small molecule docking framework via geometric deep learning with large-scale pretraining

    May 22, 2026Shi Li, Xujun Zhang, Mingquan Liu +5Structure-Based Drug DesignDrug Discovery

    College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, P. R. China · College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, P. R. China · Faculty of Health Sciences, University of Macau, Macau SAR, China +4

  8. A Large-Scale Dataset and Benchmark: Do Protein-Ligand Models Learn Binding Sites or Just Binding Likelihood?

    May 21, 2026Zhaohan Meng, Zhen Bai, Ke Yuan +4Drug Discovery

    School of Computing Science, University of Glasgow · School of Life Science and Technology, Institute of Science Tokyo · School of Cancer Sciences, University of Glasgow +4

  9. Molecular Lead Optimization via Agentic Tool Planning

    May 21, 2026Lingxiao Li, Haobo Zhang, Ruohao Fan +2Molecular OptimizationLarge Language Model-Guided Optimization

    University of Michigan Ann Arbor, Michigan, USA · Department of Biochemistry and Molecular Medicine University of California, Davis Davis, California, USA · Department of Pharmacology and Toxicology Michigan State University East Lansing, Michigan, USA

  10. SMDD-Bench: Can LLMs Solve Real-World Small Molecule Drug Design Tasks?

    May 20, 2026Kevin Han, Renfei Zhang, Kathy Wei +3LLM Agent EvaluationAI Agent Benchmarks

    Carnegie Mellon University · Stealth · Pennsylvania State University

  11. Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization

    May 17, 2026Yuan Xue, Daniel Kudenko, Megha KhoslaMolecular OptimizationDiffusion Model Fine-Tuning

    L3S Research Center, Hanover, Germany · Delft University of Technology, Delft, Netherlands

  12. DrugSAGE:Self-evolving Agent Experience for Efficient State-of-the-Art Drug Discovery

    May 14, 2026Yikun Zhang, Xiwei Cheng, Tianyu Liu +2AI Agents for Scientific DiscoveryAI-Assisted Scientific Research

    1Northeastern University · 2Broad Institute of MIT and Harvard · 3Yale University +1

  13. Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Design

    May 14, 2026Ziyu Xu, Zijian Zhang, Liang Wang +4Molecular GenerationConditional Diffusion Models

    NLPR, MAIS, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China +1

  14. ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery

    May 12, 2026Andrew Y. Zhou, Sharvaree Vadgama, Sumanth Varambally +3Drug DiscoveryAI Agents for Scientific Discovery

    Department of Computer Science and Engineering, UC San Diego, La Jolla, California, United States · Department of Computer Science, Stanford University, Stanford, California · Skaggs School of Pharmacy and Pharmaceutical Sciences, UC San Diego, La Jolla, California

  15. Decomposing the Generalization Gap in PROTAC Activity Prediction: Variance Attribution and the Inter-Laboratory Ceiling

    May 12, 2026Thor Klamt, Wolfgang Nejdl, Ming TangMolecular Property PredictionScientific Reproducibility

    L3S Research Center, Leibniz Universität Hannover, Appelstraße 9a, 30167 Hannover, Germany · Institute of Data Science (Knowledge-Based Systems), Faculty of Electrical Engineering and Computer Science,2026 Leibniz Universität Hannover, Appelstraße 9a, 30167 Hannover, Germany

  16. TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation

    May 10, 2026Hanqun Cao, Aastha Pal, Sophia Tang +4Molecular GenerationProtein Design

    Department of Computer Science and Engineering, The Chinese University of Hong Kong · Department of Bioengineering, University of Pennsylvania · Department of Computer and Information Science, University of Pennsylvania +1

  17. MolWorld: Molecule World Models for Actionable Molecular Optimization

    May 9, 2026Yang Qiao, Bo Pan, Hao-Wei Pang +3Molecular OptimizationWorld Models

    Emory University · Atlanta, GA, USA · Merck & Co., Inc. +1

  18. From Holo Pockets to Electron Density: GPT-style Drug Design with Density

    May 9, 2026Jiahao Chen, Letian Gao, Yanhao Zhu +4Structure-Based Drug Design3D Molecular Generation

    Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China · Beijing Key Laboratory of Research on Large Models and Intelligent Governance, Beijing, China · Engineering Research Center of Next Generation Intelligent Search and Recommendation, MOE, Beijing, China +3

  19. SPADE: Faster Drug Discovery by Learning from Sparse Data

    May 6, 2026Rahul Nandakumar, Ben Fauber, Deepayan ChakrabartiMolecular OptimizationAI-Assisted Scientific Research

    McCombs School of Business University of Texas at Austin Austin, TX · NVIDIA

  20. Curated AI beats frontier LLMs at pharma asset discovery

    May 6, 2026Łukasz Kidziński, Kevin ThomasLLM EvaluationHealthcare

    Gosset Research

  21. MolViBench: Evaluating LLMs on Molecular Vibe Coding

    May 4, 2026Jiatong Li, Yuxuan Ren, Weida Wang +4AI-Assisted Scientific ResearchScientific Code Generation

    The Hong Kong Polytechnic University · National University of Singapore · Fudan University

  22. Benchmarking Single-Pose Docking, Consensus Rescoring, and Supervised ML on the LIT-PCBA Library: A Critical Evaluation of DiffDock, AutoDock-GPU, GNINA, and DiffDock-NMDN

    May 3, 2026Youssef Abo-Dahab, Xiaoiang Xiang, Joanne Chun +1Learning to RankVirtual Screening

    Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California, San Francisco, San Francisco, CA, USA · UCSF–Stanford Center of Excellence in Regulatory Science and Innovation (CERSI), San Francisco, CA, USA

  23. Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction

    Apr 29, 2026Jinjiang Guo, Sheng DingLLM EvaluationMolecular Property Prediction

    Global Health Drug Discovery Institute, Beijing 100084, China · School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China

  24. Computational Design and Experimental Validation of Photoactive PARP1 Inhibitors

    Apr 27, 2026Simon Axelrod, Miroslav Kašpar, Kristýna Jelínková +8Molecular OptimizationStructure-Based Drug Design

    Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138 · Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139 · Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nám. 2, 160 00 Prague 6, Czech Republic

  25. Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance

    Apr 27, 2026Shiyun Wa, Yifei Wang, Simone Sciabola +1Molecular GenerationMolecular Representation Learning

    Biogen, Cambridge, MA, USA

  26. CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation

    Apr 25, 2026Thibaud Southiratn, Bonil Koo, Yijingxiu Lu +1Monte Carlo Tree SearchMolecular Generation

    Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea · Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea · AIGENDRUG Co., Ltd., Seoul, Republic of Korea +1

  27. h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network

    Apr 25, 2026Yanru Qu, Yijie Zhang, Wenjuan Tan +6Protein-Ligand Binding Affinity PredictionHierarchical Representation Learning

    Department of Computer Science, UIUC · School of Computer Science, McGill University · MILA-Québec AI Institute +4

  28. HBGSA: Hydrogen Bond Graph with Self-Attention for Drug-Target Binding Affinity Prediction

    Apr 25, 2026Junxiao Kong, Chupei Tang, Di Wang +4Protein-Ligand Binding Affinity PredictionGraph Neural Networks

    School of Mathematics and Statistics, Lanzhou University, 222 South Tianshui Road, 730000, Gansu, China · Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong 999077, China

  29. C-MORAL: Controllable Multi-Objective Molecular Optimization with Reinforcement Alignment for LLMs

    Apr 24, 2026Rui Gao, Youngseung Jeon, Swastik Roy +2RL for Language ModelsMolecular Optimization

    University of California, Los Angeles · Amazon

  30. BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature

    Apr 23, 2026Jiaxian Yan, Jintao Zhu, Yuhang Yang +8Document Information ExtractionMultimodal Large Language Models

    State Key Laboratory of Cognitive Intelligence, University of Science and Technology of China · Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University · Princeton University +2