3D Molecular Generation

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This field develops models that generate molecular topology and 3D atom coordinates, either from scratch or conditioned on protein pockets, fragments, spectra, or desired properties. Common approaches include SE(3)-equivariant diffusion and flow matching, autoregressive graph generation, latent-space models, and energy-based sampling. Methods are evaluated on benchmarks such as QM9, GEOM-Drugs, and CrossDocked using chemical validity, geometric stability, diversity, property scores, and binding-pose quality. A central challenge is balancing fast, controllable generation with physically stable and diverse molecules that retain realistic distributions and can be synthesized.

Latest papers

55 papers5 papers in the last four weeks, down 37% on the four weeks before. 0.0% of all new papers.

EVA-Flow: Learning Shared Chemistry for Unified Environment-Aware Molecular Conformation Generation
Oct 26, 2026Bing Yan, Anuroop Sriram, Zachary Ward Ulissi +33D Molecular Generation Molecular Generation
FAIR at Meta · New York University
MLIPDiff: Guiding Denoising Diffusion Models for Structure-Based Drug Design via Machine-Learned Interatomic Potentials
Oct 23, 2026Yiyan Liao, Amin Tavakoli, Yu Zhang +1Structure-Based Drug Design Diffusion Model Guidance
Caltech
ADT: All-Atom Diffusion Tokenizer for 3D Molecular Structures
Oct 16, 2026Xuantuo Huang, Encheng Su, Aoran Wang +6Protein Structure Generation 3D Molecular Generation
Peking University · University of Science and Technology of China · Shanghai AI Laboratory +1
OctMole: Multiscale 3D Molecular Generation with Hierarchical Spatial Flows
Oct 12, 2026Yu-Tong Jin, Yi-Yang Tian, Qiwei Ye +13D Molecular Generation Generative Modeling
Peking University · Beijing Academy of Artificial Intelligence
MAST: Motif-Augmented Diffusion with Search Tree for Spectroscopic Molecular Structure Elucidation
Oct 8, 2026Chenghao Jia, Mengdi Liu, Hong Chang +2Molecular Generation Diffusion Sampling
State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, China · University of Chinese Academy of Sciences, China
RIDE: Reference-Anchored Inference-Time Diffusion Editing for Scaffold Hopping
Sep 28, 2026Ruoxi Gao, Frazier N. Baker, Trieu Nguyen +1Diffusion Guidance Structure-Based Drug Design
Department of Computer Science and Engineering, The Ohio State University · Department of Biomedical Informatics, The Ohio State University · Translational Data Analytics Institute, The Ohio State University +1
TreeRef-BFN: Equivariance-Free De Novo Molecule Generation based on 2D Topology and Internal 3D Geometry
Sep 26, 2026Ruiqing Sun, Sen Yang, Dawei Feng +33D Molecular Generation Conditional Generative Modeling
College of Computer Science and Technology National University of Defense Technology Changsha 410073, China · Bioinformatics Center of AMMS Beijing 100080, China
Budgeted Quotient-Residual Guidance for Frozen Pocket-Conditioned Molecular Diffusion
Sep 25, 2026Xinyu Wang, Jinbo Bi, Minghu SongDiffusion Guidance Molecular Generation
Department of Computer Science and Engineering, University of Connecticut Storrs, CT 06269, USA · Institute of Health and Medicine, Hefei Comprehensive National Science Center Hefei 230601, China
QALPA: Property-guided diffusion modeling for efficient exploration of chemical spaces of flexible molecules
Sep 15, 2026Michael Hanna, Julian Cremer, Zekiye Erarslan +1Molecular Generation 3D Molecular Generation
Faculty of Computer Science, TUD Dresden University of Technology, 01062 Dresden, Germany · Machine Learning & Computational Sciences, Pfizer Worldwide R&D, Berlin, Germany · Center for Advanced Systems Understanding (CASUS), Conrad-Schiedt-Straße 20, Görlitz 02826, Germany +2
Ensemble-Conditioned Molecular Design
Sep 14, 2026Ross Irwin, Alessandro Tibo, Jon Paul Janet +1Molecular Optimization Structure-Based Drug Design
Molecular AI Discovery Sciences, R&D AstraZeneca Gothenburg, Sweden · Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Gothenburg, Sweden
Fixed-Dimensional Latent Flow for Generating Variable-Size 3D Molecules
Sep 8, 2026Weichi Yao, Cameron Gruich, Bryan R. Goldsmith +13D Molecular Generation Molecular Generation
Michigan Institute for Data & AI in Society · Department of Chemical Engineering, University of Michigan, Ann Arbor, USA · Department of Statistics, University of Michigan, Ann Arbor, USA
PocketVE: Stable and Property-Guided Structure-Based Drug Design with Variance-Exploding Diffusion
Sep 8, 2026Peining Zhang, Jinbo BiDiffusion Model Guidance Structure-Based Drug Design
University of Connecticut Storrs, Connecticut 06269, USA
NEAT-POCKET: Pocket-Conditioned Autoregressive 3D Molecular Generation with a Neighborhood-Guided Set Transformer
Sep 4, 2026Roxane Axel Jacob, Daniel Rose, Thierry Langer +13D Molecular Generation Molecular Generation
Department of Pharmaceutical Sciences, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria. · Christian Doppler Laboratory for Molecular Informatics in the Biosciences, Department of Pharmaceutical Sciences, Faculty of Life Sciences, Josef-Holaubek-Platz 2, 1090 Vienna, Austria. · Vienna Doctoral School of Pharmaceutical, Nutritional and Sport Sciences (PhaNuSpo), Josef-Holaubek-Platz 2, 1090 Vienna, Austria.
Language-Informed Flow Matching for Trend-Guided Structure-Based 3D Molecular Generation
Aug 31, 2026Tianyu Gao, Zhikai Su, Jiashu Li +5Flow Matching Structure-Based Drug Design
1City University of Hong Kong · 2The University of Hong Kong · 3Stanford University
SE(3)-MeanFlow: Few-Step Protein Backbone Generation on Lie Groups
Jul 29, 2026Yikun Bai, Binghang Lu, Yikai Liu +7Flow Matching Lie Group Methods
Department of Mathematics, Purdue University · School of Electrical and Computer Engineering, Purdue University · Department of Biochemistry, Purdue University +5
Boltzmann-Expected Molecular Design with Decoupled Annealing Flows
Jul 21, 2026Selma Moqvist, Richard Beckmann, Ross Irwin +2Molecular Optimization Molecular Graph Generation
Department of Computer Science and Engineering Chalmers University of Technology & University of Gothenburg SE-41296 Gothenburg, Sweden · Molecular AI Discovery Sciences, R&D AstraZeneca SE-43183 Mölndal, Sweden
Do Language Models Dream of Binding Molecules? Benchmarking LLMs under Spatial Constraints
Jul 20, 2026Thomas MacDougall, Maksim Kuznetsov, Roman Schutski +5Constrained Generative Modeling LLM Evaluation
Insilico Medicine Canada Inc. · Insilico Medicine Hong Kong Ltd. · Insilico Medicine AI Limited
SinAE: A Single-Architecture Flow-Matching Autoencoder for Cross-Domain Atomic Systems
Jul 14, 2026Yuxuan Ren, Fan Yang, Jianhua Yao +1Autoencoders 3D Molecular Generation
Department of Computer Science National University of Singapore · Tencent AI for Life Science Lab
Generating Developable 3D Molecules via Pocket-Conditioned Diffusion and Property-Aware Optimization
Jul 14, 2026Ruoxi Gao, Jiangweizhi Peng, Ziqi Chen +10Molecular Optimization Structure-Based Drug Design
Computer Science and Engineering, The Ohio State University, Columbus, OH 43210. · Industrial and System Engineering, University of Minnesota, Minneapolis, MN 55455. · Google Cloud, Google LLC, Mountain View, CA 94043. +6
Autoregressive latent diffusion for 3D molecule generation
Jul 10, 2026Federico Ottomano, Gaopeng Ren, Yingzhen Li +2Latent Diffusion Models Molecular Graph Generation
Department of Chemistry Imperial College London · Department of Computing Imperial College London
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Jul 1, 2026Miruna Cretu, John Bradshaw, Patricia Suriana +6Latent Diffusion Models 3D Molecular Generation
University of Cambridge, Cambridge, UK · Prescient Design (AI for Drug Discovery), Genentech, South San Francisco, USA · Work done during an internship at Prescient Design
Sesame: Structure-Aware Molecular Generation via Spatial Density-Map Conditioning
Jun 22, 2026Konstantin Yatsenko, Arvind ThiagarajanMolecular Generation Structure-Based Drug Design
Tessel Biosciences, Inc., 750 Main Street, Cambridge, MA 02139
Multigrid Training for Molecular Generation using Graph Neural Networks
Jun 21, 2026Zixuan Ling, Paula Mercurio, Di LiuStructure-Based Drug Design 3D Molecular Generation
Department of Mathematics, Michigan State University, East Lansing, MI. · Department of Mathematics, Hamline University, Saint Paul, MN.
Emyx: Fast and efficient all-atom protein generation
Jun 12, 2026Nicholas J. Williams, Ward Haddadin, Matteo P. Ferla +6Conditional Flow Matching 3D Molecular Generation
Xyme, Oxford, UK
Smoothing Dark Areas in Molecular Latent Diffusion
Jun 11, 2026Xi Wang, Jiahan Li, Yuxuan Xia +3Variational Autoencoders Latent Diffusion Models
New York University · Stanford University
Uncertainty Estimation for Molecular Diffusion Models
Jun 11, 2026Paul Seij, Christian A. Naesseth, Stephan Mandt +13D Molecular Generation Molecular Generation
UvA-Bosch Delta Lab, University of Amsterdam · University of California, Irvine
Few-step Cofolding with All-Atom Flow Maps
Jun 7, 2026Gianluca Scarpellini, Ron Shprints, Peter Holderrieth +7Protein Structure Prediction Diffusion Distillation
1Genesis Molecular AI · Massachusetts Institute of Technology · Carnegie Mellon University +2
Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport
Jun 5, 2026Malte Franke, Stefan P. Schmid, Zarko Ivkovic +2Molecular Optimization Molecular Graph Generation
ETH Zürich · NCCR Catalysis
ProHiFlo: Hierarchical Flow Matching with Functional Guidance for De Novo Protein Generation
Jun 3, 2026Chuanzhen Wang, Meade Cleti, Pete JanoFlow Matching 3D Molecular Generation
3Tongji University · 1Arizona State University · University of Wisconsin-Madison
Uncertainty-Calibrated Diffusion for Reliable 3D Molecular Graph Generation
Jun 1, 2026Fang Wan, Jingxiang Qu, Yi LiuDiffusion Sampling Molecular Graph Generation
State University of New York at Stony Brook

Oct 26, 2026J/K move · Enter open · S save

EVA-Flow: Learning Shared Chemistry for Unified Environment-Aware Molecular Conformation Generation

Bing Yan, Anuroop Sriram, Zachary Ward Ulissi, Kyunghyun Cho+2

FAIR at Meta · New York University

3D Molecular Generation Molecular Generation Conformer Conditional Generative Modeling Flow-Based Generative Modeling

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Molecular 3D structures underpin simulations of thermodynamics, kinetics, crystallization, and nucleation, making their accurate prediction central to drug discovery and materials design. However, molecular geometry can change dramatically across environments. Existing models either ignore environmental effects or train separate models for each environment. We hypothesize that transfer learning across contexts is possible for conformer generation and that a general model will perform better when training data are limited, as in ligand binding and crystallization. We introduce EVA-Flow, a unified framework for environment-aware molecular conformation generation that learns shared chemical structure and adapts it through environment-conditioned generative modeling. Across vacuum, protein-ligand docking, solvation, and crystal packing, pretraining and cross-environment finetuning provide their largest gains in the three data-scarce settings. Evaluation against multiple reference conformations shows that EVA-Flow covers a broad range of solvation conformations. Analyses of molecules shared across environments support its ability to generate different conformations for the same molecule in different environments.