Molecular Generation

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16 papers in the last four weeks, up 220% on the four weeks before. 0.2% of all new papers.

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Deep Learning for Protein Complex Prediction and Design
May 11, 2026Ziwei XieProtein Structure Prediction Molecular Generation
TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO, Chicago, Illinois
FORGE: Fragment-Oriented Ranking and Generation for Context-Aware Molecular Optimization
May 11, 2026Qingchuan Zhang, He Cao, Hao Li +6Molecular Optimization Large Language Model-Guided Optimization
University of Science and Technology of China · International Digital Economy Academy · Peking University +5
ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design
May 11, 2026Yulin Zhang, He Cao, Zihao Jiang +6Protein Language Models Multi-Teacher Knowledge Distillation
Tsinghua University · International Digital Economy Academy · Hong Kong University of2026 Science and Technology (Guangzhou) +1
TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation
May 10, 2026Hanqun Cao, Aastha Pal, Sophia Tang +4Molecular Generation 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 +1
MolWorld: Molecule World Models for Actionable Molecular Optimization
May 9, 2026Yang Qiao, Bo Pan, Hao-Wei Pang +3Molecular Optimization World Models
Emory University · Atlanta, GA, USA · Merck & Co., Inc. +1
From Holo Pockets to Electron Density: GPT-style Drug Design with Density
May 9, 2026Jiahao Chen, Letian Gao, Yanhao Zhu +4Structure-Based Drug Design 3D Molecular Generation
Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China · Beijing Key Laboratory of Research on Large Models and Intelligent Governance, Beijing, China · Engineering Research Center of Next Generation Intelligent Search and Recommendation, MOE, Beijing, China +3
Toward Better Geometric Representations for Molecule Generative Models
May 8, 2026Shaoheng Yan, Zian Li, Cai Zhou +3Geometric Representation Learning 3D Molecular Generation
Institute for Artificial Intelligence, PKU · ByteDance AI Drug Discovery · School of Intelligence Science and Technology, PKU +3
Unlocking High-Fidelity Molecular Generation from Mass Spectra via Dual-Stream Line Graph Diffusion
May 7, 2026Xujun Che, Xiuxia Du, Depeng XuGraph Neural Networks Molecular Graph Generation
Department of Software and Information Systems,2026 University of North Carolina at Charlotte, Charlotte, NC 28223 · Center for Environmental Monitoring and Informatics Technologies for Public Health University of North Carolina at Charlotte, Charlotte, NC 28223 · Department of Bioinformatics and Genomics,May University of North Carolina at Charlotte, Charlotte, NC 28223
FlashMol: High-Quality Molecule Generation in as Few as Four Steps
May 7, 2026Xinyuan Wei, Zian Li, Shaoheng Yan +2Diffusion Distillation Few-Step Diffusion Sampling
Institute for Artificial Intelligence, Peking University · Yuanpei College, Peking University · School of Intelligence Science and Technology, Peking University +2
SMolLM: Small Language Models Learn Small Molecular Grammar
May 7, 2026Akhil Jindal, Harang JuSmall Language Models Mechanistic Interpretability
Moku
Molecules Meet Language: Confound-Aware Representation Learning and Chemical Property Steering in Transformer-VAE Latent Spaces
May 7, 2026Zakaria Elabid, Jan Andrzejewski, Bartosz Brzoza +1Variational Autoencoders Molecular Generation
Helmholtz-Zentrum Dresden-Rossendorf Center for Advanced Systems Understanding
Confidence is the key: how conformal prediction enhances the generative design of permeable peptides
May 7, 2026Laura van Weesep, Sunay Chankeshwara, Leonardo De Maria +3Molecular Generation
Molecular AI, Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Mölndal, Sweden. · Department of Information Technology, Uppsala University, Sweden · Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, The Netherlands. +3
Conditional generation of antibody sequences with classifier-guided germline-absorbing discrete diffusion
May 7, 2026Justin Sanders, Luca Giancardo, Lan Guo +4Diffusion Model Guidance Protein Language Models
Paul G. Allen School of Computer Science and Engineering, University of Washington · ∗Work performed during internship at Amazon Web Services · Life Sciences, Amazon Web Services
Expanding functional protein sequence space using high entropy generative models
May 5, 2026Roberto Netti, Emily Hinds, Francesco Calvanese +3Molecular Generation Protein Design
Sorbonne Universit´e, CNRS, Department of Computational, Quantitative and Synthetic Biology—CQSB, 75005 Paris, France · Center for Physics of Evolving Systems, University of Chicago, Chicago, IL, USA · Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA +4
A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion
May 5, 2026Chaoran Cheng, Jiaqi Guan, Milong Ren +5Generative Modeling Molecular Generation
University of Illinois Urbana-Champaign · 2ByteDance Seed
Protein-Conditioned Multi-Objective Reinforcement Learning for Full-Length mRNA Design
May 2, 2026Zixi Shao, Tao Wang, Yibei Xiao +1Multi-Objective Reinforcement Learning Molecular Generation
Nanjing Foreign Language School, Nanjing, China · School of Science, China Pharmaceutical University, Nanjing, China · School of Pharmacy, China Pharmaceutical University, Nanjing, China
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 +26Generative Modeling 3D Molecular Generation
Stanford University
VQ-SAD: Vector Quantized Structure Aware Diffusion For Molecule Generation
May 1, 2026Farshad Noravesh, Reza Haffari, Layki Soon +1Latent Diffusion Models Vector-Quantized Variational Autoencoder
Towards A Generative Protein Evolution Machine with DPLM-Evo
Apr 30, 2026Xinyou Wang, Liang Hong, Jiasheng Ye +4Protein Language Models Molecular Generation
ByteDance Seed · Nanjing University · CUHK +1
Generative structure search for efficient and diverse discovery of molecular and crystal structures
Apr 30, 2026Yifang Qin, Yu Shi, Junfu Tan +3Crystal Structure Prediction Crystal Structure Generation
School of Computer Science, Peking University Beijing, 100871, China. · 2Zhongguancun Academy, Beijing, 100094, China. · School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, 30332, Georgia, USA. +1
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
Advancing Ligand-based Virtual Screening and Molecular Generation with Pretrained Molecular Embedding Distance
Apr 27, 2026Shiyun Wa, Yifei Wang, Simone Sciabola +1Molecular Generation Molecular Representation Learning
Biogen, Cambridge, MA, USA
BiMol-Diff: A Unified Diffusion Framework for Molecular Generation and Captioning
Apr 27, 2026Aditya Hemant Shahane, Anuj Kumar Sirohi, Devansh Arora +3Diffusion Sampling Molecular Generation
Indian Institute of Technology Delhi · Indian Institute of Technology Ropar · Indian Institute of Science Bengaluru
CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation
Apr 25, 2026Thibaud Southiratn, Bonil Koo, Yijingxiu Lu +1Monte Carlo Tree Search Molecular Generation
Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea · Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea · AIGENDRUG Co., Ltd., Seoul, Republic of Korea +1
Quotient-Space Diffusion Models
Apr 23, 2026Yixian Xu, Yusong Wang, Shengjie Luo +4Generative Modeling 3D Molecular Generation
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
Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design
Apr 22, 2026Wengyu Zhang, Xiao-Yong Wei, Qing LiAI-Assisted Scientific Research Multi-Agent Debate
♠The Hong Kong Polytechnic University · ♡Sichuan University
Multi-Objective Reinforcement Learning for Generating Covalent Inhibitor Candidates
Apr 21, 2026Renee GilMolecular Optimization Molecular Generation
Independent Researcher
Structure-guided molecular design with contrastive 3D protein-ligand learning
Apr 21, 2026Carles Navarro, Philipp Tholke, Gianni de FabritiisContrastive Learning Virtual Screening
Acellera Labs, C/ Doctor Trueta 183, 08005 Barcelona, Spain · Computational Science Laboratory, Universitat Pompeu Fabra, PRBB, C/ Doctor Aiguader 88, 08003 Barcelona, Spain · Instituci´o Catalana de Recerca i Estudis Avan¸cats (ICREA), Passeig Llu´ıs Companys 23, 08010 Barcelona, Spain
An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PepPI and TC-PepGen
Apr 20, 2026Chupei Tang, Junxiao Kong, Moyu Tang +5Molecular Generation Conditional Generative Modeling
School of Mathematics and Statistics, Lanzhou University, 222 South Tianshui Road, Lanzhou 730000, Gansu, China · Cuiying Honors College, Lanzhou University, Lanzhou, Gansu, China · Shanghai Innovation Institute, Shanghai, China +1

May 11, 2026, cs.LGJ/K move · Enter open · S save

Deep Learning for Protein Complex Prediction and Design

Ziwei Xie

TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO, Chicago, Illinois

Protein Structure Prediction Molecular Generation Protein Design

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Accurately modeling and designing protein complex structures is a central problem in computational structural biology, with broad implications for understanding cellular function and developing therapeutics. This thesis investigates two fundamental aspects of this problem using deep learning: domain-specific architectures that capture the hierarchical nature of protein structures, and search algorithms that efficiently navigate the vast sequence spaces of protein complexes to identify interacting homologs for improving complex structure prediction and to design protein sequences.

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Latest papers 172