Molecular Foundation Models

Follow this topic Ask about this topic

Latest papers

25 papers5 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Molecular Prior Networks
Nov 3, 2026Pawel Gomoluch, Anthony BradleyProtein-Ligand Binding Affinity Prediction Molecular Foundation Models
DaltonTx · Department of Chemistry, University of Liverpool
Attribution-based diagnostics for single-cell foundation models
Nov 2, 2026Farnoush Rezaei Jafari, Tristan Lazard, Kenza Bouzid +6Feature Attribution Molecular Foundation Models
BIFOLD - Berlin Institute for the Foundations of Learning and Data · Technical University of Berlin · BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, Germany +1
DELBERT-2: Pretrained Fingerprint Language Models for DEL Protein Binder Prediction
Oct 30, 2026Bing Hu, Sun Sun, Shaik Salman Basha +2Drug Discovery Molecular Foundation Models
Computer Science, University of Waterloo, Canada · National Research Council of Canada, Canada · Applied Mathematics, University of Waterloo, Canada +1
General-purpose foundation models surpass specialized ones on chemical property prediction tasks
Oct 30, 2026Stepan N. Ostarkov, Gregorii A. Semakin, Ivan A. Bespalov +1Molecular Property Prediction Chemical Language Models
N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Science, 119334, Moscow, Russia
Ensemble-Aware Structural Encoding (EASE): Conditioning Protein Encoders on Peptide Conformational Ensembles
Oct 20, 2026Ruoyao Zhang, Hongxuan Li, Jie Peng +1Protein Representation Learning Molecular Property Prediction
University of Waterloo · University of North Carolina at Chapel Hill
ProtGlycanDock: Towards Accurate Protein-Glycan Docking with Tailored Dataset, Benchmark and Model
Oct 19, 2026Minghao Xu, Jiaze Song, Jinyu Wang +1Molecular Foundation Models
Peking University · University of Chinese Academy of Sciences · Zhongguancun Academy +1
What DNA Foundation Models Learn Beyond Sequence Composition
Oct 11, 2026Vincenzo Yuto Civale, Andrew David Bagdanov, Alberto MagiGenomic Foundation Models Molecular Foundation Models
University of Florence
When Do Biological Reasoning Models Use Their Biological Inputs?
Oct 1, 2026Ada Fang, Nikitha Thoduguli, Lukas Fesser +3Faithfulness of Language Model Explanations Causal Interventions in Language Models
Harvard University · Massachusetts Institute of Technology
A General-Purpose Molecular Foundation Model Transfers Across Diverse Olfactory Tasks
Aug 26, 2026Yikun Han, Yi Wang, Neil Mankodi +2Molecular Foundation Models Transfer Learning
Department of Statistics, University of Michigan, Ann Arbor, Michigan, USA · Computer Science and Engineering Division, University of Michigan, Ann Arbor, Michigan, USA
Mol-JEPA: A multimodal Joint Embedding Predictive Architecture for Molecules
Aug 23, 2026Florian Rottach, Sebastian Schieferdecker, William Rudman +2Joint-Embedding Predictive Architecture Multimodal Pretraining
University of Tübingen · 2Boehringer Ingelheim · 3The University of Texas at Austin +1
Monroe: A Molecular Foundation Model for In-Context Probabilistic Inference
Aug 19, 2026Blazej Banaszewski, Andrew W. FitzgibbonMolecular Foundation Models Molecular Representation Learning
Graphcore, Bristol, UK · Max Planck Institute of Biochemistry, Munich, DE · Graphcore, Cambridge, UK
Domain-Adapted Molecular Language Models for Efficient Search of Make-on-Demand Libraries
Aug 18, 2026Henrik Wille, Luis-Finley Schütz, Felix Strieth-KalthoffMolecular Representation Learning Molecular Foundation Models
University of Wuppertal, School of Mathematics and Natural Sciences, Gaußstr. 20, 42119 Wuppertal, Germany · University of Wuppertal, Interdisciplinary Center of Machine Learning and Data Analytics, Gaußstr. 20, 42119 Wuppertal, Germany
Folding, Reasoning, and Scaling with Open-source Drug Discovery Engine
Jul 4, 2026Aureka AI OpenDDE projectProtein Structure Prediction Molecular Foundation Models
OpenDDE Project, Aureka AI Research
BioMatrix: Towards a Comprehensive Biological Foundation Model Spanning the Modality Matrix of Sequences, Structures, and Language
Jun 20, 2026Qizhi Pei, Zhimeng Zhou, Yi Duan +9Multimodal Understanding Multimodal Pretraining
1Gaoling School of Artificial Intelligence, Renmin University of China, 2OpenDataLab, Shanghai Artificial Intelligence Laboratory · 3Zhejiang University, 4Shanghai Innovation Institute · 2OpenDataLab, Shanghai Artificial Intelligence Laboratory, 3Zhejiang University, 4Shanghai Innovation Institute +5
AMix-2: Establishing Protein as a Native Modality in Large Language Models
May 29, 2026Keyue Qiu, Yixin Wu, Lihao Wang +19Diffusion Language Models Protein Language Models
1Shanghai Artificial Intelligence Laboratory · Institute for AI Industry Research (AIR), Tsinghua University
Controllable Molecular Generative Foundation Models
May 14, 2026Yihan Zhu, Yuhan Liu, Weijiang Li +2RL for Diffusion Models Molecular Graph Generation
University of Notre Dame
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 Evaluation Molecular Property Prediction
Global Health Drug Discovery Institute, Beijing 100084, China · School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
MIMIC: A Generative Multimodal Foundation Model for Biomolecules
Apr 27, 2026Siavash Golkar, Jake Kovalic, Irina Espejo Morales +28Molecular Generation Genomics
Polymathic AI · Center for Data Science, New York University · Department of Applied Physics, Yale University +17
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 Prediction Molecular Foundation Models
The University of Hong Kong, Hong Kong SAR · Nanyang Technological University, Singapore · University of Cambridge, United Kingdom +4
Tabular foundation models for in-context prediction of molecular properties
Apr 17, 2026Karim K. Ben Hicham, Jan G. Rittig, Martin Grohe +1Tabular Foundation Models Molecular 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
Suiren-1.0 Technical Report: A Family of Molecular Foundation Models
Mar 23, 2026Junyi An, Xinyu Lu, Yun-Fei Shi +5Molecular Foundation Models Molecular Representation Learning
Shanghai Academy of AI for Science (SAIS)
MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery
Mar 3, 2026Maksim Kuznetsov, Zulfat Miftahutdinov, Rim Shayakhmetov +17Molecular Optimization Molecular Property Prediction
Insilico Medicine · Liquid AI
Information Routing in Atomistic Foundation Models: How Task Alignment and Equivariance Shape Linear Disentanglement
Mar 3, 2026Joshua SteierMolecular Representation Learning Representation Disentanglement
Independent Researcher
D3LM: A Discrete DNA Diffusion Language Model for Bidirectional DNA Understanding and Generation
Mar 2, 2026Zhao Yang, Hengchang Liu, Chuan Cao +1Molecular Foundation Models Genomic Foundation Models
Gaoling School of Artificial Intelligence, Renmin University of China · Zhongguancun Academy
MACE-POLAR-1: A Polarisable Electrostatic Foundation Model for Molecular Chemistry
Feb 23, 2026Ilyes Batatia, William J. Baldwin, Domantas Kuryla +10Molecular Foundation Models Machine Learning Interatomic Potentials
Engineering Laboratory, University of Cambridge, Trumpington St, Cambridge, UK · Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK · Cavendish Laboratory, University of Cambridge, J. J. Thomson Avenue, Cambridge, UK +6

Nov 3, 2026J/K move · Enter open · S save

Molecular Prior Networks

Pawel Gomoluch, Anthony Bradley

DaltonTx · Department of Chemistry, University of Liverpool

Protein-Ligand Binding Affinity Prediction Molecular Foundation Models In-Context Learning Prior-Data Fitted Networks

Open paper AskPDF arXiv

Predicting affinity between small molecules and their protein targets remains one of the central problems in drug discovery. Due to the substantial cost of wet-lab experiments, machine learning models of drug-target affinity are usually trained on relatively small datasets, ranging from tens to hundreds of molecules. Given the inherent difficulty of generalization between different targets and chemical series, existing datasets of protein-ligand affinities are typically not used for new projects. At the same time, tabular foundation models, including Prior-data Fitted Networks, have recently shown how transformers can be used to solve machine learning problems in a single forward pass of the network, after being trained over a large corpus of, typically, synthetic datasets. Inspired by that line of work, we propose a novel affinity modelling approach, in which the labels of the query molecules are predicted from the labelled support molecules in a single forward pass of a transformer model. The model is trained on thousands of existing affinity datasets, enabling it to capture the general patterns of molecular activity across different targets, chemical series and dataset sizes. For the smallest support sets, our model matches the state of the art on the regression variant of the FS-Mol benchmark, while being faster than existing methods, thanks to the lack of task-specific training. A comparison against a reduced variant of our architecture, which amounts to kernel regression in a meta-learned feature space, shows that the predictive performance of the transformer model is only partially explained by simple molecular similarity.