Protein Structure Generation

Latest papers

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

Trion-1: Unifying Language, Protein Sequence, and Structure with Diffusion Language Models
Oct 22, 2026Tianyu Lu, Kaicheng Yang, Jiangtao Feng +7Protein Language Models Protein Structure Generation
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
DC-Flow: Target-Conditioned Cyclic Peptide Design via Delayed-Coupling Flow Matching
Oct 11, 2026Yitian Wang, Minjie Cheng, Yaning Cui +3Protein Structure Generation Molecular Generation
Gaoling School of Artificial Intelligence, Renmin University of China · DP Technology · Cyclon Therapeutics +2
Designing Protein Structures from Natural Language
Oct 9, 2026Joseph Lee, Yanjing Li, Bo Qiang +7Protein Structure Generation Protein Design
University of Washington · National University of Singapore · Allen Institute for AI (Ai2) +1
Learning Latent Protein Languages for Autoregressive Generation
Oct 2, 2026Mahdi Pourmirzaei, Farzaneh Esmaili, Amir Ziashahabi +2Protein Structure Generation Protein Language Models
University of Missouri · University of Southern California · Independent Researcher
PhiFold: Towards Dynamic Protein Design with Physics-Structured Covariance Modeling
Sep 26, 2026Yutian Liu, Mujie Lin, LanqianZhang +4Protein Design Protein Structure Generation
School of Computer Science, Peking University, Beijing, China · School of Electronic and Computer Engineering, Peking University, Shenzhen, China · School of Life Sciences, Tsinghua University, Beijing 100084, China +2
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
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
DCFold: Efficient Protein Structure Generation with Single Forward Pass
May 18, 2026Zhe Zhang, Yuanning Feng, Yuxuan Song +3Protein Structure Prediction Protein Structure Generation
Institute for AI Industry Research (AIR), Tsinghua University · Department of Computer Science and Technology, Tsinghua University · School of Computer Science and Technology, Huazhong University of Science and Technology +1
Ligand-Conditioned Discrete Diffusion for Protein Sequence-Structure Co-Design
May 15, 2026Chen Wei, Fanding Xu, Minghao Sun +5Protein Language Models Diffusion Language Model Decoding
Xi’an University of Posts & Telecommunications · National University of Singapore · Xi’an Jiaotong University +1
CrystalBoltz: End-to-End Protein Structure Determination via Experiment-Guided Diffusion for X-Ray Crystallography
May 15, 2026Minseo Kim, Huanghao Mai, Jay Shenoy +3Bayesian Inverse Problems Diffusion Posterior Sampling
Stanford University · SLAC National Accelerator Laboratory · UC Davis
Yeti: A compact protein structure tokenizer for reconstruction and multi-modal generation
May 11, 2026Nabin Giri, Steven Farrell, Kristofer E. BouchardProtein Structure Generation Generative Modeling
Lawrence Berkeley National Laboratory
A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion
May 5, 2026Chaoran Cheng, Jiaqi Guan, Milong Ren +5Protein Structure Generation Generative Modeling
University of Illinois Urbana-Champaign · 2ByteDance Seed
Co-Generative De Novo Functional Protein Design
May 1, 2026Xinrui Chen, Yizhen Luo, Siqi Fan +1Protein Language Models Molecular Generation
Institute for AI Industry Research (AIR), Tsinghua University · Department of Computer Science and Technology, Tsinghua University · PharMolix Inc.
Proteo-R1: Reasoning Foundation Models for De Novo Protein Design
May 1, 2026Fang Wu, Weihao Xuan, Heli Qi +26Molecular Generation Generative Modeling
Stanford University
Quotient-Space Diffusion Models
Apr 23, 2026Yixian Xu, Yusong Wang, Shengjie Luo +4Protein Structure Generation Generative Modeling
State Key Laboratory of General Artificial Intelligence, Peking University, Beijing, China · State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University · Zhongguancun Academy, Beijing, China +2
Polyformer: a generative framework for thermodynamic modeling of polymeric molecules
Apr 15, 2026Alessio Valentini, David Pekker, Chungwen Liang +2Protein Structure Generation Protein Structure Prediction
PsiDagger, San Diego, CA · Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA · Department of Chemistry and The PULSE Institute, Stanford University, Stanford, CA +1
PI-Mamba: Linear-Time Protein Backbone Generation via Spectrally Initialized Flow Matching
Mar 17, 2026Tianyu Wu, Lin ZhuProtein Structure Generation Protein Design
Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, 600 S Mathews Ave., 61801, IL, USA · School of Information Science, University of Illinois Urbana-Champaign, 501 E Daniel St., 61820, IL, USA
Rigidity-Aware Geometric Pretraining for Protein Design and Conformational Ensembles
Mar 2, 2026Zhanghan Ni, Yanjing Li, Zeju Qiu +4Protein Structure Generation Generative Modeling
University of Illinois Urbana-Champaign · University of Washington · MPI for Intelligent Systems, Tübingen +3
SPID: Distilled Protein Backbone Generation
Oct 3, 2025Liyang Xie, Haoran Zhang, Zhendong Wang +2Diffusion Model Distillation Few-Step Diffusion Sampling
The University of Texas at Austin · The Memorial Sloan Kettering Cancer Center

Oct 22, 2026J/K move · Enter open · S save

Trion-1: Unifying Language, Protein Sequence, and Structure with Diffusion Language Models

Tianyu Lu, Kaicheng Yang, Jiangtao Feng, Keyue Qiu+6

Protein Language Models Protein Structure Generation Diffusion Language Models Protein Representation Learning Multimodal Diffusion Models Protein Structure Prediction+1

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We envision a general-purpose protein foundation model as a unified, interactive model of sequence, structure, and function, capable of understanding, generation, and cross-modal translation while retaining the instruction-following and reasoning capabilities of modern LLMs. Toward this vision, we introduce Trion-1, the first native, unified, multimodal diffusion language model (dLLM) for proteins. Trion-1 is built on two key design choices: (1) a unified discrete token space that jointly represents sequence, structure, and natural language; (2) a dLLM backbone that replaces strict left-to-right factorization with bidirectional or semi-bidirectional token interactions, enabling global residue communication and long-range contact modeling that are naturally suited to structure modeling. This formulation unifies six core capabilities: folding, inverse folding, sequence understanding, structure understanding, sequence design, and structure design, while retaining the native language capabilities of general-purpose LLMs. On established benchmarks, Trion-1 achieves broadly competitive performance. In folding, Trion-1 achieves a TM-score above 0.8 with a single sample under strict homology control, matching or exceeding the existing tri-modal model using 200 samples. For sequence understanding, Trion-1 performs on par with top-tier LLMs such as Claude Opus 4.7 (62.37%). These results support well-aligned sequence-structure-language representations and strong cross-modal generative capabilities.