Molecular Representation Learning

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Overview

Molecular representation learning studies how to encode molecules and biomolecules so models can recognize chemical structure, predict properties, and support tasks such as drug screening and molecular design. Approaches range from fingerprints and molecular graphs to SMILES language models, 3D equivariant networks, fragment-based methods, and multimodal models combining structure with spectra, text, or biological measurements. Self-supervised and contrastive pretraining are common ways to learn from unlabeled structures, while supervised models use task-specific labels for properties such as solubility, binding affinity, or toxicity. A central challenge is reliable transfer to new chemical scaffolds and biological settings: larger pretrained models do not always beat simpler fingerprints or descriptors, and results depend strongly on data splits, representation choices, and whether physical and chemical information is preserved.

Latest papers

CardsList

207 papers23 papers in the last four weeks, up 5% on the four weeks before. 0.1% of all new papers.

  1. A Comparative Study of QSPR Methods on a Unique Multitask PAMPA dataset

    May 1, 2026Andrs Formanek, Anna Vincze, Richrd Bicsak +3Multi-Task LearningMolecular Property Prediction

    Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems,May Signal Processing and Data Analytics, KU Leuven, 3001 Leuven, Belgium · Department of Artificial Intelligence and Systems Engineering, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Műegyetem rkp. 3, H-1111 Budapest, Hungary[cs.LG] · Department of Chemical and Environmental Process Engineering, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3, H-1111 Budapest, Hungary +2

  2. VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation

    May 1, 2026Farshad Noravesh, Reza Haffari, Layki Soon +1Latent Diffusion ModelsVector-Quantized Variational Autoencoder

  3. Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models

    May 1, 2026Jiaxin Qi, Hang Li, Yan Cui +2Gene Regulatory Network InferenceSingle-Cell Transcriptomics

    Computer Network Information Center, Chinese Academy of Sciences, Beijing, China · Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China · University of Chinese Academy of Sciences, Beijing, China

  4. Hyper-Dimensional Fingerprints as Molecular Representations

    Apr 30, 2026Jonas Teufel, Luca Torresi, André Eberhard +1Hyperdimensional ComputingMolecular Property Prediction

    Karlsruhe Institute of Technology (KIT), Institute of Nanotechnology (INT), Kaiserstraße 12, Karlsruhe, Germany. · Karlsruhe Institute of Technology (KIT), Institute of Anthropomatics and Robotics (IAR), Kaiserstraße 12, Karlsruhe, Germany.

  5. Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement

    Apr 29, 2026Zuriel Y. Yescas-Ramos, Andrés Álvarez-García, Huziel E. SaucedaQuantum ChemistryEquivariant Neural Networks

    Instituto de Física, Universidad Nacional Autónoma de México, Cd. de México C.P. 04510, Mexico

  6. 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

  7. MIMIC: A Generative Multimodal Foundation Model for Biomolecules

    Apr 27, 2026Siavash Golkar, Jake Kovalic, Irina Espejo Morales +28Molecular GenerationGenomics

    Polymathic AI · Center for Data Science, New York University · Department of Applied Physics, Yale University +17

  8. 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

  9. 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

  10. Drug Synergy Prediction via Residual Graph Isomorphism Networks and Attention Mechanisms

    Apr 23, 2026Jiyan Song, Wenyang Wang, Chengcheng Yan +2Graph Neural NetworksGraph Representation Learning

    College of Sciences, Shihezi University, 221 North 4th Road, Shihezi, 832003, Xinjiang, China · School of Mathematics and Computational Science, Xiangtan University, North 2nd Ring Road, Xiangtan, 411105, Hunan, China

  11. Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning

    Apr 22, 2026Yuhan Peng, Junwen Dong, Yuzhi Zeng +6Graph Neural NetworksGeometric Representation Learning

    School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore · Chern Institute of Mathematics, Nankai University, Tianjin, China · Department of Mathematics, Faculty of Science, National University of Singapore, Singapore +3

  12. A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era

    Apr 17, 2026Zongru Li, Xingsheng Chen, Honggang Wen +8Molecular Property PredictionMolecular Foundation Models

    The University of Hong Kong, Hong Kong SAR · Nanyang Technological University, Singapore · University of Cambridge, United Kingdom +4

  13. Tabular foundation models for in-context prediction of molecular properties

    Apr 17, 2026Karim K. Ben Hicham, Jan G. Rittig, Martin Grohe +1Tabular Foundation ModelsMolecular Property Prediction

    RWTH Aachen University, Process Systems Engineering (AVT.SVT), Aachen, Germany. · Lehrstuhl Informatik 7, RWTH Aachen University, Aachen, Germany. · JARA-CSD, Aachen, Germany. +1

  14. An Interpretable Framework Applying Protein Words to Predict Protein-Small Molecule Complementary Pairing Rules

    Apr 17, 2026Jingke Chen, Jingrui Zhong, Tazneen Hossain Tani +3Protein-Ligand Binding Affinity PredictionInterpretable ML

    MOE Key Laboratory of Bioinformatics, State Key Laboratory of Molecular Oncology, Beijing Frontier Research Center for Biological Structure, School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China

  15. ReadMOF: Structure-Free Semantic Embeddings from Systematic MOF Nomenclature for Machine Learning

    Apr 12, 2026Kewei Zhu, Cameron Wilson, Bartosz Mazur +3Molecular Representation LearningMaterials Science

    Department of Chemical Engineering, University College London, London WC1E 7JE, United Kingdom · Department of Micro, Nano, and Bioprocess Engineering, Faculty of Chemistry, Wroclaw University of Science and Technology, Wroclaw 50-370, Poland · Manufacturing Futures Lab, University College London, 7 Sidings Street, London, E20 2AE, United Kingdom

  16. NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning

    Apr 12, 2026Yanyi Su, Hongshuai Wang, Zhifeng Gao +1Representation LearningMolecular Representation Learning

    State Key Laboratory of Physical Chemistry of Solid Surface, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China · DP Technology · Laboratory of AI for Electrochemistry (AI4EC), Tan Kah Kee Innovation Laboratory (IKKEM), Xiamen, China +1

  17. When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction

    Apr 8, 2026Bryan Cheng, Jasper ZhangMolecular Property PredictionMolecular Representation Learning

    Great Neck South High School

  18. BiScale-GTR: Fragment-Aware Graph Transformers for Multi-Scale Molecular Representation Learning

    Apr 7, 2026Yi Yang, Ovidiu DaescuMolecular Representation LearningGraph Transformer

    Department of Computer Science, The University of Texas at Dallas

  19. MolDA: Molecular Understanding and Generation via Large Language Diffusion Model

    Apr 6, 2026Seohyeon Shin, HanJun Choi, Jun-Hyung Park +2Multimodal Large Language ModelsMolecular Graph Generation

    Gwangju Institute of Science and Technology, Gwangju, South Korea · Hankuk University of Foreign Studies, Seoul, South Korea

  20. Entropy, Disagreement, and the Limits of Foundation Models in Genomics

    Apr 5, 2026Maxime Rochkoulets, Lovro Vrček, Mile ŠikićGenomic Foundation ModelsGenomics

    Genome Institute of Singapore, A*STAR, Singapore · KU Leuven, Belgium · Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia

  21. VIANA: character Value-enhanced Intensity Assessment via domain-informed Neural Architecture

    Apr 1, 2026Luana P. Queiroz, Icaro S. C. Bernardes, Ana M. Ribeiro +2Dose-Response EstimationMolecular Representation Learning

    LSRE-LCM, ALiCE, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal · Department of Chemical Engineering, Norwegian University of Science and Technology, Sem Sælands vei 4, NO-7491 Trondheim, Norway · Corporate Fragrance R&D, The Procter & Gamble Company, Ivorydale Innovation Center, 5299 Spring Grove Ave., Cincinnati, OH 45140, USA +1

  22. Generative Chemical Language Models for Energetic Materials Discovery

    Mar 30, 2026Andrew Salij, R. Seaton Ullberg, Megan C. Davis +5Molecular GenerationMaterials Science

    Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA · Weapon Stockpile Modernization Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA · Computing and Artificial Intelligence Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

  23. ChemCLIP: Bridging Organic and Inorganic Anticancer Compounds Through Contrastive Learning

    Mar 30, 2026Mohamad Koohi-Moghadam, Hongzhe Sun, Hongyan Li +1Cancer Drug Response PredictionMolecular Representation Learning

    Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam Road, Hong Kong SAR, PR China · Department of Chemistry, The University of Hong Kong, Pok Fu Lam Road, Hong Kong S.A.R., PRC

  24. What an Autonomous Agent Discovers About Molecular Transformer Design: Does It Transfer?

    Mar 30, 2026Edward WijayaNeural Architecture SearchTransfer Learning

    StemRIM, Inc.

  25. Distilling Genomic Models for Efficient mRNA Representation Learning via Embedding Matching

    Mar 27, 2026Rasched Haidari, Sam Martin, Maxime AllardKnowledge DistillationMolecular Representation Learning

    Helical London, UK

  26. SIGMA: Semantic Identifier Grouping for Molecular Autoregression

    Mar 26, 2026Xinyu Wang, Fei Dou, Jinbo Bi +1Molecular GenerationMolecular Representation Learning

    School of Computing, University of Connecticut, Storrs, CT, USA · Institute for Artificial Intelligence, University of Georgia, Athens, GA, USA · Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China

  27. DeepDTF: Dual-Branch Transformer Fusion for Multi-Omics Anticancer Drug Response Prediction

    Mar 25, 2026Yuhan Zhao, Jacob Tennant, James Yang +3Multi-Omics Data IntegrationCancer Drug Response Prediction

    Department of Computer Science, North Carolina State University, Raleigh, NC, USA · UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA · Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, USA

  28. ZeroFold: Protein-RNA Binding Affinity Predictions from Pre-Structural Embeddings

    Mar 24, 2026Josef Hanke, Sebastian Pujalte Ojeda, Shengyu Zhang +3Molecular Property PredictionMolecular Representation Learning

    Yusuf Hamied Department of Chemistry, University of Cambridge, UK · Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK · Medicinal Chemistry, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R and D, AstraZeneca, Sweden +1

  29. Suiren-1.0 Technical Report: A Family of Molecular Foundation Models

    Mar 23, 2026Junyi An, Xinyu Lu, Yun-Fei Shi +5Molecular Foundation ModelsMolecular Representation Learning

    Shanghai Academy of AI for Science (SAIS)

  30. DMMRL: Disentangled Multi-Modal Representation Learning via Variational Autoencoders for Molecular Property Prediction

    Mar 22, 2026Long Xu, Junping Guo, Jianbo Zhao +2Molecular Representation LearningMultimodal Disentangled Representation Learning

    Guangxi Key Lab of Human-machine Interaction and Intelligent Decision, Nanning Normal University, Nanning, China · College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, China