Protein Design

Latest papers 97

23 papers in the last four weeks, up 188% on the four weeks before. 0.1% of all new papers.

Leveraging generative hallucination and biophysics-informed modeling for unified biomolecular sequence-structure co-design
Aug 18, 2026Xuefeng Liu, Mingxuan Cao, Xiao Luo +5Protein Design Molecular Generation
Department of Medicine, University of Florida · Department of Computer Science, University of Chicago · Data Science Institute, University of Chicago +5
Protein Structure Prediction: From Evolutionary Constraints to Generative Modeling
Aug 17, 2026Wengan He, Yongsheng Luo, Lihong Jiang +2Protein Structure Prediction Protein Representation Learning
Zhuhai College of Science and Technology, Zhuhai, China · Zhuhai UNO Technology Co., Ltd., Zhuhai, China
Genotypic Triggers: Exposing Pharmacogenomic Blind Spots via Host-Specific Backdoors in Generative Antimicrobial Peptide Models
Aug 7, 2026Doniyorkhon Obidov, Xiaolong Guo, Yonghui Li +1Backdoor Attacks Molecular Generation
Michigan Technological University · Lehigh University · Kansas State 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
Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling
Jul 26, 2026Hengyuan Cao, Shizhuo Cheng, Mingxuan Liu +5Molecular Generation Protein Design
Zhejiang University, Hangzhou, China · Fudan University, Shanghai, China · Shanghai Institute for Advanced Study Zhejiang University, Shanghai, China +1
Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design
Jul 22, 2026Xiaoliang Shi, Zichen Wang, Runze Ma +2Multimodal Pretraining Protein Design
Shanghai Jiao Tong University
ABOPD: Antibody CDR Design via On-Policy Distillation
Jul 21, 2026Zhuo Yang, Jiaying He, Jiaqing Xie +5Diffusion Model Distillation On-Policy Distillation
Shanghai Innovation Institute · Southeast University · Zhejiang University +4
Variable-Length Generative Protein Design via Generalized Poisson Flow
Jul 10, 2026Chaoran Cheng, Zhanghan Ni, Yanru Qu +4Generative Modeling Flow-Based Generative Modeling
Siebel School of Computing and Data Science University of Illinois Urbana-Champaign
Design-CP: Context Parallelism for Design of Protein Nanoparticles
Jul 3, 2026Lorenzo Tarricone, Helen E. Eisenach, Aiko Muraishi +1GPU Acceleration High-Performance Computing
Department of Statistics, University of Oxford, Oxford, UK · Ellison Institute of Technology Oxford, Oxford, UK · Institute for Protein Design, University of Washington, Seattle, USA +2
Diffeomorphic Optimization
Jul 1, 2026Ludwig Winkler, Andrew Leaver-Fay, Joseph Kleinhenz +1Riemannian Optimization Protein Design
Microsoft Research AI4Science · Prescient Design, Genentech Roche
Two-Stage Fine-Tuning for Protein Sequence Generation with Targeted Amino-Acid Composition
Jun 26, 2026Violeta Basten-Romero, Rubén Muñoz-Tafalla, Anna María Díaz-Rovira +3Protein Language Models Protein Design
Barcelona Supercomputing Center (BSC), Plaça d’Eusebi Güell, 1-3, 08034, Barcelona, Spain · Department of Bioinformatics, School of Mathematics and Statistics (FME), Universitat Politècnica de Catalunya - BarcelonaTech (UPC), 08034 Barcelona, Spain · Nostrum Biodiscovery S.L., Av. Josep Tarradellas, 8-10, 3-2, 08029, Barcelona, Spain +1
Pepti-drift: Scalable Safe-Active Peptide Generation Without Inference-Time Guidance
Jun 26, 2026Takashi Fujiwara, Hikaru Shindo, Kaushalya Madhawa +6Molecular Generation Protein Design
Department of AI Systems Medicine Institute of Integrated Research Institute of Science Tokyo · SB Intuitions Tokyo, JAPAN
Scalable Peptide Design via Memory-Efficient Equivariant Transformer
Jun 23, 2026Rui Jiao, Xiangzhe Kong, Yinjun Jia +4Equivariant Neural Networks Efficient Attention
Department of Computer Science and Technology, Tsinghua University · Institute for AI Industry Research, Tsinghua University · Department of Electronic Engineering, Tsinghua University +1
Be Your Own Teacher: Steering Protein Language Models via Unsupervised Reward Optimization
Jun 17, 2026Lanqing Li, Shentong Mo, Yang Yu +1RL for Language Models Reinforcement Learning
The Chinese University of Hong Kong · MBZUAI · Hong Kong University of Science and Technology
Pepti-Agent: An AI Agent for Peptide Design and Optimization
Jun 13, 2026Houxu Chen, Achuth Chandrasekhar, Amir Barati FarimaniAI Agents for Scientific Discovery Large Language Model-Guided Optimization
Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA · Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA · Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA +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
DeepRHP: A Hybrid Variational Autoencoder for Designing Random Heteropolymers as Protein Mimics
Jun 10, 2026Shuni Li, Zhiyuan Ruan, Andy Shen +3Variational Autoencoders Protein Design
University of California Berkeley; Berkeley, California, 94720, USA.
VFUSE: Virulent Feature Understanding with Sparse autoEncoders
Jun 8, 2026Michael Yu, Matthew L. OlsonSparse Autoencoders Mechanistic Interpretability
Raft Bioworks · Independent
AlloGen: Conformation-Selective Binder Generation with Differential State Scoring
Jun 3, 2026Hanqun Cao, Zachary Quinn, Aastha Pal +4Protein-Protein Interaction Prediction Protein Design
Department of Computer Science and Engineering, The Chinese University of Hong Kong · Department of Bioengineering, University of Pennsylvania · Department of Computer and Information Science, University of Pennsylvania
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
AgentPLM: Agentic Protein Language Models with Reasoning-Augmented Decoding for Protein Sequence Design
Jun 1, 2026Sahil Rahman, Maxx Richard RahmanRL for Language Models Direct Preference Optimization
Bedford College, London, United Kingdom · Saarland University, Saarbrücken, Germany
Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling
Jun 1, 2026Keyue Qiu, Xintong Wang, Zhilong Zhang +2Multimodal Generation Molecular Generation
Institute for AI Industry Research (AIR), Tsinghua University · Department of Computer Science and Technology, Tsinghua University · Qiuzhen College, Tsinghua University +1
TadA-Bench: A Million-Variant Benchmark for Future-Round Discovery Toward Agentic Protein Engineering
May 29, 2026Jin Gao, Juntu Zhao, Zirui Zeng +5Protein Fitness Prediction Benchmark Design
Shanghai Jiao Tong University · Shanghai Innovation Institute.
AMix-2: Establishing Protein as a Native Modality in Large Language Models
May 29, 2026Keyue Qiu, Yixin Wu, Lihao Wang +19Multimodal Large Language Models Protein Language Models
1Shanghai Artificial Intelligence Laboratory · Institute for AI Industry Research (AIR), Tsinghua University
Self-Improvement Imitation with Biologically Guided Search for Protein Design Under Oracle Budgets
May 26, 2026Ashima Khanna, Dominik GrimmSurrogate-Assisted Optimization Black-Box Optimization
Bioinformatics, Technical University of Munich, TUM Campus Straubing, 94315 Straubing, Germany · University of Applied Sciences Weihenstephan-Triesdorf, 94315 Straubing, Germany
SurfDesign: Effective Protein Design on Molecular Surfaces
May 25, 2026Fang Wu, Shuting Jin, Xiangru Tang +5Protein Design Molecular Representation Learning
Stanford University Stanford, USA · Wuhan University of Science and Technology Wuhan, China · Yale University New Haven, USA +5
AgForce Enables Antigen-conditioned Generative Antibody Design
May 20, 2026Mansoor Ahmed, Murray PattersonProtein Design Conditional Generative Modeling
1Georgia State University, Atlanta, GA, USA · 2Georgia Institute of Technology, Atlanta, GA, USA
ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning
May 20, 2026Mansoor Ahmed, Spencer VonBank, Nadeem Taj +3Protein Design
Georgia State University, Atlanta, USA · Georgia Institute of Technology, Atlanta, USA · DePauw University, Indiana, USA +2
EvoStruct: Bridging Evolutionary and Structural Priors for Antibody CDR Design via Protein Language Model Adaptation
May 20, 2026Mansoor Ahmed, Sujin Lee, Umar Khayaz +1Protein Language Models Equivariant GNNs
Georgia State University, Atlanta, USA · Georgia Institute of Technology, Atlanta, USA
DCFold: Efficient Protein Structure Generation with Single Forward Pass
May 18, 2026Zhe Zhang, Yuanning Feng, Yuxuan Song +3Protein Structure Prediction AI-Assisted Scientific Research
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

Aug 18, 2026J/K move · Enter open · S save

Leveraging generative hallucination and biophysics-informed modeling for unified biomolecular sequence-structure co-design

Xuefeng Liu, Mingxuan Cao, Xiao Luo, Songhao Jiang+4

Department of Medicine, University of Florida · Department of Computer Science, University of Chicago · Data Science Institute, University of Chicago+5

Protein Design Molecular Generation Physics-Informed Generative Modeling

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Biomolecular design underpins applications from molecular recognition to therapeutics and synthetic biology, yet de novo interaction design remains challenging-especially for DNA/RNA, underexplored non-protein modalities with scarce, heterogeneous complex data and sharper geometric and chemical constraints. We introduce MCTH (Monte Carlo Tree Hallucination), an inference-only framework that casts all-atom sequence-structure co-design as uncertainty-aware planning over hallucinated states from pretrained folding and inverse-folding models, with optional biophysical control within the same decision loop. MCTH treats these models as frozen black-box operators and uses Monte Carlo Tree Search to allocate a fixed inference budget across competing design trajectories, incorporating model confidence and uncertainty, as well as cross-expert consensus/disagreement when multiple predictors are available. Across protein-RNA, protein-DNA, protein-protein, and protein-ligand design, matched-budget experiments show that adaptive search improves over simpler sampling and cycling strategies, while held-out AlphaFold3 and Chai-1 evaluations demonstrate transfer beyond the search-time oracle. MCTH provides a shared planning layer across modalities while allowing task-specific folding, inverse-folding, and biophysical modules, requiring no fine-tuning or backpropagation through component models.