Molecular Property Prediction

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Overview

Molecular property prediction studies how to infer quantities such as solubility, toxicity, binding affinity, and quantum energies from molecules, mixtures, or molecular environments. Common approaches use fingerprints and physicochemical descriptors, graph neural networks, molecular language models, and 3D equivariant or multimodal models; some also encode physical laws or learn from experimental and simulated data together. Models are assessed on benchmarks such as MoleculeNet and TDC, with scaffold, temporal, and other out-of-distribution splits used to test transfer to unfamiliar chemistry. A central challenge is that strong in-distribution scores and larger pretrained models do not guarantee reliable extrapolation, while careful classical baselines, data quality, uncertainty estimates, and evaluation design can strongly affect results.

Latest papers

CardsList

204 papers29 papers in the last four weeks, level with the four weeks before. 0.2% of all new papers.

  1. Transformer-inspired architectures make machine-learned electron densities accurate and transferable enough to bypass self-consistency

    Oct 29, 2026Jeheon WooDensity Functional TheoryMolecular Property Prediction

    Center for AI and Natural Sciences, Korea Institute for Advanced Study, Seoul 02455, Republic of Korea

  2. Where the Error Lives: Spectral Representations of Learned Kohn-Sham Hamiltonians

    Oct 27, 2026Fang Sun, Hekai Cheng, Ruoyan Li +4Density Functional TheoryMolecular Property Prediction

    Computer Science Department, University of California, Los Angeles

  3. Learning atomic interactions for the thermodynamics of liquid mixtures

    Oct 27, 2026Marco Hoffmann, Sebastian Schmitt, Hans Hasse +1Molecular Property PredictionGraph Neural Networks

    RPTU Kaiserslautern-Landau, Kaiserslautern

  4. Stationarity Constraints Improve Both Energies and Densities of Machine-Learned Exchange-Correlation Functionals

    Oct 21, 2026Yuhao Chen, Donald G. Truhlar, Xiao HeDensity Functional TheoryComputational Quantum Chemistry

    Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China · Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431, USA · Anhui Provincial Key Laboratory of Advanced Catalysis and Energy Materials, Anhui Ultra High Molecular Weight Polyethylene Fiber Engineering Research Center, School of Chemistry and Chemical Engineering, Anqing Normal University, Anqing 261433, China +1

  5. Fragment-Level Graph Encoding for Interpretable Molecular Property Prediction

    Oct 21, 2026Rafael Lopes Almeida, Ina PöhnerMolecular Property PredictionGNN Explainability

    School of Pharmacy, University of Eastern Finland, Kuopio, Finland

  6. SU(2)-Equivariant Spinor Message Passing for Molecular Magnetism

    Oct 21, 2026Erh-Wei Sheng, Beom Seok Kang, Yuchao Lin +2Equivariant GNNsMolecular Property Prediction

    Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California 91125, USA · Department of Chemical Engineering, National Tsing Hua University, Hsinchu 300044, Taiwan · Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA

  7. Ensemble-Aware Structural Encoding (EASE): Conditioning Protein Encoders on Peptide Conformational Ensembles

    Oct 20, 2026Ruoyao Zhang, Hongxuan Li, Jie Peng +1Protein Representation LearningMolecular Property Prediction

    University of Waterloo · University of North Carolina at Chapel Hill

  8. PRISM: Prior Relational Information for Self-supervised Modeling to Enhance Solubility OOD Generalization

    Oct 19, 2026Xinyi Chen, Jiahuan Pang, Titus Chima +2Molecular Property PredictionSelf-Supervised Pre-Training

    Global College, Shanghai Jiao Tong University, Shanghai, China. · Digital Innovation Research Center, Duke Kunshan University, Kunshan, Jiangsu, China. · Zu Chongzhi Center, Duke Kunshan University, Kunshan, Jiangsu, China. +1

  9. M-JEPA: Predictive Self-Supervised Learning for Molecular Graphs with Scaffold-Shift Evaluation on Tox21

    Oct 18, 2026Karthik Iyer, Nasser SabarGraph SSLMolecular Representation Learning

    Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC 3086, Australia

  10. Not All Unlabeled Data Are Equal: Unlabeled Data Selection for Semi-Supervised QSAR Modeling with Large Chemical Repositories

    Oct 15, 2026Oliver Majer, Saso Dzeroski, Jurica LevaticTraining Data SelectionSemi-Supervised Learning

    Jožef Stefan Institute, Jamova cesta 39, Ljubljana, Slovenia · University of Ljubljana, Faculty of Computer and Information Science, Večna pot 113, Ljubljana, Slovenia

  11. Beyond Benchmark Accuracy: A Diagnostic Test for LLM Chemical Prediction

    Oct 14, 2026Yanyi Su, Yu Zeng, Hongshuai Wang +3Chemical Reasoning in LLMsRetrosynthesis

    State Key Laboratory of Physical Chemistry of Solid Surface, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China · DP Technology, Beijing, China

  12. ProtModernBERT: Compute-Efficient Protein Language Modeling

    Oct 14, 2026Alberto Martínez, Natalia Flechas Manrique, Llorenç Espinosa-Portalés +1Protein Language ModelsEfficient Language Model Training

    Multiverse Computing, Parque Científico y Tecnológico de Gipuzkoa, Paseo de Miramón 170, 20014 Donostia-San Sebastián, Spain. · Multiverse Computing, 7 rue de la Croix Martre, 91120 Palaiseau, Paris, France

  13. Does Pretraining Teach Chemical Language Models Chemistry?

    Oct 13, 2026Leif Sieben, Yoel ZimmermannChemical Language ModelsLanguage Model Pretraining

    Harvard University, Cambridge, MA, USA

  14. Solvating machine-learning interatomic potentials for solution-phase chemistry

    Oct 12, 2026Anton Z. Ni, Joonho LeeMachine Learning Interatomic PotentialsMolecular Property Prediction

    Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA

  15. Electron-Density-Informed Molecular Property Prediction Using Surrogate Functionals

    Oct 9, 2026Manuel V. Klockow, Simon Wagner, Roman Remme +2Density Functional TheoryMolecular Property Prediction

    Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University 69120 Heidelberg, Germany

  16. Physics-Aligned Electronic Ground-State Learning Improves Generalization

    Oct 7, 2026Eike S. Eberhard, Xaver Kainz, Viktor Kotsev +2Physics-Informed MLOOD Generalization

    Technical University of Munich (TUM) · Munich Data Science Institute (MDSI) · Munich Center for Machine Learning (MCML) +1

  17. Atom-JEPA: Joint-Embedding Predictive Architecture for 3D Atomistic Systems

    Oct 6, 2026Kasper Helverskov Petersen, Rasmus Hannibal Tirsgaard, François R J Cornet +2Joint-Embedding Predictive ArchitectureMaterials Property Prediction

    Department of Applied Mathematics and Computer Science Technical University of Denmark

  18. Can phenotypic activity be predicted without experimental readouts?

    Oct 6, 2026Télio Cropsal, Rocío MercadoMolecular Property PredictionMolecular Representation Learning

    AI Laboratory for Molecular Engineering (AIME) Department of Computer Science and Engineering Chalmers University of Technology & University of Gothenburg, Gothenburg, Sweden · AI Laboratory for Molecular Engineering (AIME) Department of Computer Science and Engineering Chalmers University of Technology & University of Gothenburg and Science for Life Laboratory (SciLifeLab), Gothenburg, Sweden

  19. Mathematical Invariant-Enabled Topological Neural Networks for Molecular and Materials Property Prediction

    Oct 6, 2026Yiming Ren, Xiang Liu, Mustafa Hajij +2Materials Property PredictionMolecular Property Prediction

    Department of Mathematics, University of Georgia, Athens, GA 30602, USA. · Department of Data Science, University of San Francisco, CA 94117, USA. · Department of Computer Science and Technology, Cambridge University, Cambridge, United Kingdom. +2

  20. Few-Shot Bioactivity Prediction with Meta-Learning under Assay Heterogeneity

    Oct 5, 2026Michal Kmicikiewicz, Tommy Rochussen, Vincent Fortuin +1Meta-LearningFew-Shot Learning

    Institute of AI for Health, Helmholtz Munich · School of Computation, Information and Technology, Technical University of Munich · Munich Center for Machine Learning +4

  21. Variational Quantum Attention for Molecular Graph Learning

    Oct 3, 2026Yu-Cheng Lin, Yu-Chao Hsu, Tai-Yue Li +2Graph Attention NetworksQuantum Machine Learning

    Department of Electrophysics, National Yang Ming Chiao Tung University, Hsinchu 300092, Taiwan. · Department of Internal Medicine, School of Medicine College of Medicine, Taipei Medical University, Taipei, Taiwan · School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea +2

  22. Electronic Density versus Geometry for Machine-Learned Molecular Absorption Spectra

    Oct 2, 2026Siddharth Dhanpal, Peter Elliott, Paolo Emilio Trevisanutto +2Molecular Property PredictionMolecular Representation Learning

    Scientific Computing Department, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Didcot OX11 0QX, United Kingdom. · Scientific Computing Department, Science and Technology Facilities Council, Daresbury Laboratory, Warrington, WA4 4AD, United Kingdom.

  23. Equivariant Flow Matching for Electron Density Prediction

    Oct 2, 2026Chenxing Liang, Chengdong Wang, Yuchao Lin +2Computational Quantum ChemistryQuantum Chemistry

    Department of Computer Science and Engineering, Texas A&M University · Department of Materials Science and Engineering, Texas A&M University · Department of Electrical and Computer Engineering, Texas A&M University +2

  24. TasteBench: Multimodal Benchmark for Sensory Prediction, from Molecules to Sustainable Foods

    Oct 1, 2026Anna T. Thomas, Sohum Patnaik, Caroline Cotto +1Benchmark DesignLearning to Rank

    Stanford Computer Science · Food Intelligence Lab · NECTAR +1

  25. DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction

    Oct 1, 2026Vansh Ramani, Har Ashish Arora, Dhairya Kuchhal +2Molecular Property PredictionInterpretable ML

    1Indian Institute of Technology, Delhi, India.

  26. StabilityArc: Decoding Protein Sequence Embeddings into Generalizable Stability Landscapes

    Sep 30, 2026Aaron L. Feller, Andrew D. Ellington, Claus O. WilkeTransfer LearningMolecular Property Prediction

    The University of Texas at Austin, Interdisciplinary Life Sciences · The University of Texas at Austin, Integrative Biology

  27. Molecular Property Prediction under Structural Shift with Tabular Foundation Models

    Sep 30, 2026Jinmo Lee, Dooho Lee, Minho Jeong +1Tabular Foundation ModelsMolecular Property Prediction

    Nums AI

  28. Benchmarking graph-based models for in-silico toxicity prediction in drug discovery

    Sep 29, 2026Noel Suarez-Barro, Manuel Lama, Juan C. VidalDrug DiscoveryGraph Representation Learning

  29. MoTIF-X: A Multimodal Tokenized Framework for Interpretable and Extensible Molecular Representation Learning

    Sep 29, 2026Linqing Mo, Jiayu Zhou, Bin ChenMolecular Representation LearningCross-Modal Representation Learning

    Department of Computer Science and Engineering, Michigan State University, East Lansing, 48824, MI, USA. · School of Information, University of Michigan, Ann Arbor, 48109, MI, USA. · Department of Pediatrics and Human Development, Michigan State University, Grand Rapids, MI, 49503, USA. +2

  30. AssayRouter: Historical Utility Priors for Frozen Molecular Predictor Routing

    Sep 29, 2026Dong Xu, Zhangfan Yang, Jiantao Wu +5Adaptive Model RoutingTask Transferability Estimation

    School of Artificial Intelligence, Shenzhen University · EasternDawn · School of Computer Science, University of Nottingham Ningbo