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Drug Design

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Showing 251–300 of 440 papers

TitleStatusHype
PrefixMol: Target- and Chemistry-aware Molecule Design via Prefix Embedding—0
3D Molecular Generation via Virtual Dynamics—0
Transfer Learning for Bayesian Optimization: A Survey—0
Protein-protein docking using a tensor train black-box optimization method—0
Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy—0
Persistent Dirac for molecular representation—0
StriderNET: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes—0
Domain-Agnostic Molecular Generation with Chemical FeedbackCode1
Geometric Graph Learning with Extended Atom-Types Features for Protein-Ligand Binding Affinity PredictionCode0
Critical review of conformational B-cell epitope prediction methodsCode0
Synthesis-driven design of 3D molecules for structure-based drug discovery using geometric transformers—0
EDoG: Adversarial Edge Detection For Graph Neural Networks—0
SVSBI: Sequence-based virtual screening of biomolecular interactionsCode0
Multi-modal Molecule Structure-text Model for Text-based Retrieval and EditingCode2
xTrimoABFold: De novo Antibody Structure Prediction without MSA—0
Protein Language Models and Structure Prediction: Connection and ProgressionCode1
Reinforced Genetic Algorithm for Structure-based Drug DesignCode1
Probabilistic thermal stability prediction through sparsity promoting transformer representation—0
An Efficient MCMC Approach to Energy Function Optimization in Protein Structure PredictionCode0
A Systematic Survey of Chemical Pre-trained ModelsCode2
Exploring Data-Driven Chemical SMILES Tokenization Approaches to Identify Key Protein-Ligand Binding Moieties—0
Structure-based Drug Design with Equivariant Diffusion ModelsCode2
Structure-based drug design with geometric deep learning—0
Equivariant Shape-Conditioned Generation of 3D Molecules for Ligand-Based Drug DesignCode1
DiffDock: Diffusion Steps, Twists, and Turns for Molecular DockingCode3
ImmunoLingo: Linguistics-based formalization of the antibody language—0
Uni-Mol: A Universal 3D Molecular Representation Learning FrameworkCode0
Exploiting Pretrained Biochemical Language Models for Targeted Drug DesignCode1
Tailoring Molecules for Protein Pockets: a Transformer-based Generative Solution for Structured-based Drug DesignCode1
HiGNN: Hierarchical Informative Graph Neural Networks for Molecular Property Prediction Equipped with Feature-Wise AttentionCode1
From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep LearningCode1
Widely Used and Fast De Novo Drug Design by a Protein Sequence-Based Reinforcement Learning Model—0
Literature Review: Graph Kernels in Chemoinformatics—0
Learning programs with magic valuesCode1
A Ligand-and-structure Dual-driven Deep Learning Method for the Discovery of Highly Potent GnRH1R Antagonist to treat Uterine Diseases—0
Low cost prediction of probability distributions of molecular properties for early virtual screening—0
Roughness of molecular property landscapes and its impact on modellabilityCode0
Prediction of protein allosteric signalling pathways and functional residues through paths of optimised propensity—0
Autonomous Drug Design with Multi-Armed Bandits—0
A fully differentiable ligand pose optimization framework guided by deep learning and traditional scoring functionsCode1
LogGENE: A smooth alternative to check loss for Deep Healthcare Inference Tasks—0
SHREC 2022: Protein-ligand binding site recognitionCode1
ScatterSample: Diversified Label Sampling for Data Efficient Graph Neural Network Learning—0
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein PocketsCode2
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker DesignCode1
One-way Explainability Isn't The Message—0
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising AutoencodersCode1
A 3D Generative Model for Structure-Based Drug DesignCode2
Molecule Generation for Drug Design: a Graph Learning Perspective—0
Interactivity: the missing link between virtual reality technology and drug discovery pipelines—0
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