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Molecular Docking

Predicting the binding structure of a small molecule ligand to a protein, which is critical to drug design.

Description from: DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

Papers

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Showing 1–50 of 128 papers

TitleStatusHype
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose PredictionCode5
Modeling Molecular Structures with Intrinsic Diffusion ModelsCode3
DiffDock: Diffusion Steps, Twists, and Turns for Molecular DockingCode3
Atomic Convolutional Networks for Predicting Protein-Ligand Binding AffinityCode3
PocketVina Enables Scalable and Highly Accurate Physically Valid Docking through Multi-Pocket ConditioningCode2
PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross DockingCode2
Fast and Accurate Blind Flexible DockingCode2
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete LatentsCode2
FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose GenerationCode2
CovDocker: Benchmarking Covalent Drug Design with Tasks, Datasets, and SolutionsCode1
Scaling Structure Aware Virtual Screening to Billions of Molecules with SPRINTCode1
QuickBind: A Light-Weight And Interpretable Molecular Docking ModelCode1
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular DockingCode1
Understanding active learning of molecular docking and its applicationsCode1
CompassDock: Comprehensive Accurate Assessment Approach for Deep Learning-Based Molecular Docking in Inference and Fine-TuningCode1
Smiles2Dock: an open large-scale multi-task dataset for ML-based molecular dockingCode1
Protein language models are performant in structure-free virtual screeningCode1
Equivariant Scalar Fields for Molecular Docking with Fast Fourier TransformsCode1
Enhancing Ligand Pose Sampling for Molecular DockingCode1
DiffBindFR: An SE(3) Equivariant Network for Flexible Protein-Ligand DockingCode1
PLANTAIN: Diffusion-inspired Pose Score Minimization for Fast and Accurate Molecular DockingCode1
Domain-Agnostic Molecular Generation with Chemical FeedbackCode1
DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded LibrariesCode1
SHREC 2022: Protein-ligand binding site recognitionCode1
Direct Molecular Conformation GenerationCode1
DOCKSTRING: easy molecular docking yields better benchmarks for ligand designCode1
Assigning Confidence to Molecular Property PredictionCode1
DEEPScreen: high performance drug–target interaction prediction with convolutional neural networks using 2-D structural compound representationsCode1
ReassembleNet: Learnable Keypoints and Diffusion for 2D Fresco Reconstruction—0
Multi-Ligand Simultaneous Docking Analysis of Moringa Oleifera Phytochemicals Reveals Enhanced BCL-2 Inhibition via Synergistic Action—0
Prediction of Novel CXCR7 Inhibitors Using QSAR Modeling and Validation via Molecular Docking—0
Computational Analysis using Multi-ligand Simultaneous Docking of Withaferin A and Garcinol Reveals Enhanced BCL-2 and AKT-1 Inhibition—0
In Silico Prediction and Validation of LmGt Inhibitors Using QSAR and Molecular Docking Approaches—0
Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning—0
Generative Modeling on Lie Groups via Euclidean Generalized Score Matching—0
Docking-Aware Attention: Dynamic Protein Representations through Molecular Context Integration—0
Group Ligands Docking to Protein Pockets—0
AI Model for Predicting Binding Affinity of Antidiabetic Compounds Targeting PPAR—0
PLD-Tree: Persistent Laplacian Decision Tree for Protein-Protein Binding Free Energy Prediction—0
In Silico Pharmacokinetic and Molecular Docking Studies of Natural Plants against Essential Protein KRAS for Treatment of Pancreatic Cancer—0
GNNAS-Dock: Budget Aware Algorithm Selection with Graph Neural Networks for Molecular Docking—0
Dockformer: A transformer-based molecular docking paradigm for large-scale virtual screening—0
RapidDock: Unlocking Proteome-scale Molecular Docking—0
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active LearningCode0
WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction—0
To Explore the Potential Inhibitors against Multitarget Proteins of COVID 19 using In Silico Study—0
Allium Vegetables Intake and Digestive System Cancer Risk: A Study Based on Mendelian Randomization, Network Pharmacology and Molecular Docking—0
Generative Model for Small Molecules with Latent Space RL Fine-Tuning to Protein Targets—0
Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking Scores—0
Diffusion Models in De Novo Drug Design—0
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