Protein-Ligand Binding Affinity Prediction

Follow this topic Ask about this topic

Latest papers 23

5 papers in the last four weeks, up 25% on the four weeks before. 0.0% of all new papers.

All topics

Blending experimental electron density information to protein-ligand interaction
Oct 10, 2026Seonghyun Park, Shuan Chen, Jun Jin Choong +6Molecular Representation Learning Representation Learning
KAIST · SB Intuitions
Beyond Random Splits: Evaluating Drug-Target Affinity Models Under Chemically and Biologically Motivated Distribution Shifts Copy
Oct 2, 2026Minjae Chung, Clara Li, Malar Paavai Muthukumaran +8Protein-Ligand Binding Affinity Prediction Distribution Shift Robustness
Georgia Institute of Technology
Mirror-Score: Calibrated, Inference-only Scoring Exposes the Limits of Sequence-compatibility Ranking in D-peptide Design
Sep 28, 2026Jiada LiProtein-Ligand Binding Affinity Prediction Protein Design
AI Scientist, Albany, NY, USA, 12205
Adapting Boltz-2 with limited experimental activity data improves early enrichment in virtual screening
Sep 21, 2026Kairi Furui, Masahito OhueProtein-Ligand Binding Affinity Prediction Virtual Screening
Department of Computer Science, School of Computing, Institute of Science Tokyo, Yokohama 226-8501, Japan
CurvFlow-DTA: dual-graph discrete Ricci curvature flow for drug--target affinity prediction
Sep 19, 2026Jicheng Ma, Yunyan Yang, Juan Zhao +1Protein-Ligand Binding Affinity Prediction Drug Discovery
School of Mathematics, Renmin University of China, Beijing, 100872, China · School of Mathematical Sciences, Key Laboratory of Mathematics and Complex Systems of MOE, Beijing Normal University, Beijing, 100875, China
Chemical and geometric representation fidelity improves drug--target affinity prediction
Sep 2, 2026Yixiao Li, Yining Qian, Yefan Chen +5Protein-Ligand Binding Affinity Prediction Representation Learning
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China · School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China · School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China +1
Deploying DeepSeek 175B Locally on a Single Consumer-Grade RTX 4060 Laptop with 32GB RAM for 200k-Scale Protein-Ligand Virtual Screening
Aug 31, 2026Rui Xiao, Yili XuProtein-Ligand Binding Affinity Prediction Virtual Screening
Hangzhou Tsingxin quantum Co., Ltd.
Benchmarking Peptide-Protein Affinity Prediction Across Peptide and Target Shifts
Aug 31, 2026Jiaxin Tian, Darren An, Jun LiProtein-Ligand Binding Affinity Prediction OOD Generalization
College of Biology, Hunan University, Changsha, Hunan, China · 2Lingang Laboratory, Shanghai, China
DPTM-DT: Dual-Pretrained Transformer Multitask Representation Learning for Drug-Target Prediction
Aug 28, 2026Ge KongProtein-Ligand Binding Affinity Prediction Multi-Task Learning
School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
Recent Advances in Deep Learning-Based Drug-Target Binding Affinity Prediction
Aug 13, 2026Jafin Khan, Md Hossain ShuvoProtein-Ligand Binding Affinity Prediction Drug Discovery
Department of Computer Science, Prairie View A&M University, Prairie View, Texas, USA.
RAVEN: Frozen Random Graph Reservoirs with Physics-Informed Interaction Fingerprints for Protein-Ligand Binding Affinity Prediction
Aug 10, 2026Qingyang Zou, Jiaye Huang, Hangbo Xie +3Protein-Ligand Binding Affinity Prediction Graph Neural Networks
School of Science, China Pharmaceutical University, Nanjing, 210009, China · School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
DBMol: Design of High-Affinity, Target-Specific Small Molecules through Structure Prediction Models
Jul 21, 2026Yiming Qin, Kai Yi, Miruna Cretu +3Protein-Ligand Binding Affinity Prediction Molecular Optimization
EPFL, Switzerland · MRC-LMB, UK · University of Cambridge, UK
Trustworthy Protein-Ligand Binding Affinity Prediction via Reliability-Aware Multi-Engine Fusion
Jul 20, 2026Yongchan Hong, Defu Cao, Wenjin Liu +6Protein-Ligand Binding Affinity Prediction Evidential Deep Learning
Department of Quantitative & Computational Biology University of Southern California Los Angeles, California, USA · Department of Computer Science University of Southern California Los Angeles, California, USA · Department of Chemistry University of California, Berkeley Berkeley, California, USA
Q-Score: A Quantum-Native Scoring Function for Molecular Docking
Jul 2, 2026Kangyu Zheng, Yidong Zhou, Ruihao Li +3Protein-Ligand Binding Affinity Prediction Structure-Based Drug Design
Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin, N.T., Hong Kong SAR · Department of Electrical and Computer Engineering Rutgers University Piscataway, NJ · Computational Life Sciences Cleveland Clinic Cleveland, OH +1
Curvature-Informed Potential Energy Surface for Protein-Ligand Binding Affinity Prediction
Jun 12, 2026Peng-Fei Sun, Chuan-Xian Ren, Hong YanProtein-Ligand Binding Affinity Prediction Graph Neural Networks
School of Mathematics, Sun Yat-Sen University, Guangzhou, Guangdong 510275, China · Department of Electrical Engineering, City University of Hong Kong, Hong Kong
Curvature-Guided Geometric Representation for Protein-Ligand Binding Affinity Prediction
Jun 12, 2026Shuai Li, Chuan-Xian Ren, Yuhao Li +4Protein-Ligand Binding Affinity Prediction Hierarchical Representation Learning
School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China · Department of Electrical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong
Hierarchical Contrastive Learning for Multi-Domain Protein-Ligand Binding
May 19, 2026Shuo Zhang, Rongqi Hong, Huifeng Zhang +1Protein-Ligand Binding Affinity Prediction Contrastive Learning
University of Birmingham, UK
h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network
Apr 25, 2026Yanru Qu, Yijie Zhang, Wenjuan Tan +6Protein-Ligand Binding Affinity Prediction Hierarchical Representation Learning
Department of Computer Science, UIUC · School of Computer Science, McGill University · MILA-Québec AI Institute +4
HBGSA: Hydrogen Bond Graph with Self-Attention for Drug-Target Binding Affinity Prediction
Apr 25, 2026Junxiao Kong, Chupei Tang, Di Wang +4Protein-Ligand Binding Affinity Prediction Graph Neural Networks
School of Mathematics and Statistics, Lanzhou University, 222 South Tianshui Road, 730000, Gansu, China · Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong 999077, China
An Interpretable Framework Applying Protein Words to Predict Protein-Small Molecule Complementary Pairing Rules
Apr 17, 2026Jingke Chen, Jingrui Zhong, Tazneen Hossain Tani +3Protein-Ligand Binding Affinity Prediction Interpretable ML
MOE Key Laboratory of Bioinformatics, State Key Laboratory of Molecular Oncology, Beijing Frontier Research Center for Biological Structure, School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
LaPro-DTA: Latent Dual-View Drug Representations and Salient Protein Feature Extraction for Generalizable Drug--Target Affinity Prediction
Mar 16, 2026Zihan Dun, Liuyi Xu, An-Yang Lu +2Protein-Ligand Binding Affinity Prediction Molecular Representation Learning
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China · School of Artificial Intelligence, Beihang University, Beijing 100000, China · School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China
On the Reliability of AI Methods in Drug Discovery: Evaluation of Boltz-2 for Structure and Binding Affinity Prediction
Mar 2, 2026Shunzhou Wan, Xibei Zhang, Xiao Xue +1Protein-Ligand Binding Affinity Prediction Drug Discovery
Centre for Computational Science, University College London, London, WC1H 0AJ, U.K. · Advanced Research Computing Centre, University College London, London, WC1H 0AJ, U.K.
Structure-Aware Compound-Protein Affinity Prediction via Graph Neural Networks with Group Lasso Regularization
Jul 4, 2025Zanyu Shi, Yang Wang, Pathum M. Weerawarna +4Protein-Ligand Binding Affinity Prediction Molecular Property Prediction
Department of Biostatistics & Health Data Science, Indiana University Fairbanks School of Public Health, Indianapolis, 46202 IN, USA. · Department of Computer Science, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, 47405 IN, USA. · Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, 46202 IN, USA. +2

Oct 10, 2026J/K move · Enter open · S save

Blending experimental electron density information to protein-ligand interaction

Seonghyun Park, Shuan Chen, Jun Jin Choong, Noboru Kuno+5

KAIST · SB Intuitions

Molecular Representation Learning Representation Learning Protein-Ligand Binding Affinity Prediction Molecular Generation Protein Representation Learning

Open paper AskPDF arXiv

Machine learning models for protein-ligand interactions commonly rely on atomic coordinates, which are constructed by fitting molecular models to experimental electron-density maps. However, most models represent each complex as a single fitted structure, which can omit information about conformational heterogeneity, positional uncertainty, and local density support for individual atoms at binding interfaces. To fill this gap, we present CoDE, a Coordinate and Density Encoder, pre-trained on experimental density maps. We represent each binding site on a shared three-dimensional voxel grid combining atomic occupancy, experimental electron density, and its gradient magnitude. Using approximately 100K curated complexes, we pre-train a channel-wise vision transformer to jointly reconstruct masked atomic and density channels, learning a representation that integrates structural and experimental information. We evaluate the frozen encoder on two downstream tasks: (i) binding-affinity regression under leakage-controlled splits and (ii) pocket-conditioned ligand generation. Across these settings, CoDE improves over an identically pre-trained coordinate-only encoder and remains competitive with task-specific baselines, showing that density complements fitted atomic coordinates for protein-ligand interaction modeling and that the density-blended representation is useful for structure-based ligand generation.