Image de couverture de livre

Learning to Dock: Geometric Deep Learning for Predicting Supramolecular Host-Guest Complexes

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Zidi, Zhang, Tao, Yu, Muyao, Zhou, Chuyi, Xu, Zezhao, Liu, Huiyu, Wen, Yuzhen, Chen, Linjiang, Zheng, Jie, Jiang, Shan
Format:	Preprint
Publié:	2026
Sujets:	Chemical Physics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Guest Editorial: Special Topic on Software for Atomistic Machine Learning
par: Rupp, Matthias, et autres
Publié: (2024)

Geometric Deep Learning for Molecular Crystal Structure Prediction
par: Kilgour, Michael, et autres
Publié: (2023)

Lightweight Geometric Deep Learning for Molecular Modelling in Catalyst Discovery
par: Geitner, Patrick
Publié: (2024)

A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
par: Ji, Shengjiao, et autres
Publié: (2025)

Fluorescence and Relaxation Dynamics of Cesium in Argon Matrices: Multiple Trapping Sites and Host-Guest Interactions
par: Lahs, S., et autres
Publié: (2026)

Latent Diffusion-Based 3D Molecular Recovery from Vibrational Spectra
par: Wu, Wenjin, et autres
Publié: (2026)

Enhanced Sampling of Protein Conformational Changes via True Reaction Coordinates from Energy Relaxation
par: Li, Huiyu, et autres
Publié: (2024)

Quantum-Inspired Machine Learning for Molecular Docking
par: Shu, Runqiu, et autres
Publié: (2024)

MesoNet: A Fundamental Principle for Multi-Representation Learning in Complex Chemical Systems
par: Fan, Jinming, et autres
Publié: (2025)

Network Pharmacology, Machine Learning, Molecular Docking, and Cell Experiments Reveal the Therapeutic Mechanism of Radix Rehmanniae Praeparata in Psoriasis In Vitro
par: Tingting Zhang, et autres
Publié: (2026)

Attention-Based Functional-Group Coarse-Graining: A Deep Learning Framework for Molecular Prediction and Design
par: Han, Ming, et autres
Publié: (2025)

Deep Learning for Drug–Target Interaction Prediction: A Comprehensive Review
par: Yingjun Chen, et autres
Publié: (2025)

Toward Quantum-Aware Machine Learning: Improved Prediction of Quantum Dissipative Dynamics via Complex Valued Neural Networks
par: Atif, Muhammad, et autres
Publié: (2026)

Reaction Coordinates are Optimal Channels of Energy Flow
par: Ma, Ao, et autres
Publié: (2024)

Accelerated Machine Learning Force Field for Predicting Thermal Conductivity of Organic Liquids
par: Feng, Wei, et autres
Publié: (2025)

Accelerating Complex Materials Discovery with Universal Machine-Learning Potential-Driven Structure Prediction
par: An, Yuqi, et autres
Publié: (2026)

A Novel Deep Temporal Feature Enhanced Just‐in‐Time Learning Framework for Predicting Rare Earth Component Content
par: Zhaohui Huang, et autres
Publié: (2025)

TERS-ABNet: A Deep Learning Approach for Automated Single-Molecule Structure Reconstruction with Atomic Precision from TERS Mapping
par: Cui, Jie, et autres
Publié: (2026)

In Silico Discovery of Novel Macrocyclic Inhibitor Candidates for Cruzipain (T. cruzi) via Rigid-Body Geometric Docking and ADME Profiling
par: Pirolo, Andrés Sebastián
Publié: (2026)

Deep Learning of ab initio Hessians for Transition State Optimization
par: Yuan, Eric C. -Y., et autres
Publié: (2024)

Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning
par: Zhang, He, et autres
Publié: (2023)

Atomistic Modeling of Methane and Carbon Dioxide Structure I Gas Hydrates Under Pressure: Guest Effects and Properties
par: Mathews, Samuel, et autres
Publié: (2026)

Efficient Machine Learning Approach for Yield Prediction in Chemical Reactions
par: Ghosh, Supratim, et autres
Publié: (2025)

Black-Box Uncertainty Estimation for Deep Learning Models in Atomistic Simulations
par: Fonea, Idan, et autres
Publié: (2025)

DeepMech: A Machine Learning Framework for Chemical Reaction Mechanism Prediction
par: Das, Manajit, et autres
Publié: (2025)

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
par: Min, Yaosen, et autres
Publié: (2022)

DFT Accuracy on Crystal Structure Prediction with Machine Learning Interatomic Potentials
par: Midgley, Laurence I., et autres
Publié: (2026)

Transferable Learning of Reaction Pathways from Geometric Priors
par: Nam, Juno, et autres
Publié: (2025)

Physical probes expose and alleviate chemical-environment collapse in molecular representations
par: Fang, Jiebin, et autres
Publié: (2026)

ADEPT-PolyGraphMT: Automated Molecular Simulation and Multi-Task Multi-Fidelity Machine Learning for Polymer Property Generation and Prediction
par: Alosious, Sobin, et autres
Publié: (2026)

MultiModal-Learning for Predicting Molecular Properties: A Framework Based on Image and Graph Structures
par: Wang, Zhuoyuan, et autres
Publié: (2023)

The Evolution of Machine Learning Potentials for Molecules, Reactions and Materials
par: Xia, Junfan, et autres
Publié: (2025)

SAIAME: Semi‐Parameter Adaptation Information‐Assisted Multi‐Objective Evolutionary for Protein‐Ligand Docking
par: Wei Xiao, et autres
Publié: (2025)

Measurement Reduction in Orbital-Optimized Variational Quantum Eigensolver via Orbital Compression
par: Tao, Yanxian, et autres
Publié: (2026)

Transferable Machine Learning Potential X-MACE for Excited States using Integrated DeepSets
par: Barrett, Rhyan, et autres
Publié: (2025)

PackFlow: Generative Molecular Crystal Structure Prediction via Reinforcement Learning Alignment
par: Subramanian, Akshay, et autres
Publié: (2026)

A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML
par: Marimuthu, Aravindh Nivas, et autres
Publié: (2025)

Thermodynamic Descriptors from Molecular Dynamics as Machine Learning Features for Extrapolable Property Prediction
par: Espejo, Nuria H., et autres
Publié: (2026)

Deep Learning for GWP Prediction: A Framework Using PCA, Quantile Transformation, and Ensemble Modeling
par: Rajapriya, Navin, et autres
Publié: (2024)

ReactAIvate: A Deep Learning Approach to Predicting Reaction Mechanisms and Unmasking Reactivity Hotspots
par: Hoque, Ajnabiul, et autres
Publié: (2024)