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Drug Design

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TitleStatusHype
Improving Molecular Graph Generation with Flow Matching and Optimal Transport—0
Pathway-Guided Optimization of Deep Generative Molecular Design Models for Cancer TherapyCode0
GraphXForm: Graph transformer for computer-aided molecular designCode1
Towards Cross-Modal Text-Molecule Retrieval with Better Modality AlignmentCode0
Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection LayersCode1
TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency ModelsCode0
Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug DesignCode1
SAFE setup for generative molecular design—0
ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design—0
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular DockingCode1
Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development—0
Systems-Structure-Based Drug Design—0
Diversity-Aware Reinforcement Learning for de novo Drug Design—0
Boltzmann-Aligned Inverse Folding Model as a Predictor of Mutational Effects on Protein-Protein Interactions—0
Generative Flows on Synthetic Pathway for Drug DesignCode2
Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic PlanningCode1
Geometric Representation Condition Improves Equivariant Molecule GenerationCode1
SynthFormer: Equivariant Pharmacophore-based Generation of Synthesizable Molecules for Ligand-Based Drug Design—0
Enhancing Solution Efficiency in Reinforcement Learning: Leveraging Sub-GFlowNet and Entropy Integration—0
Binding Affinity Prediction: From Conventional to Machine Learning-Based Approaches—0
FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling—0
PepINVENT: Generative peptide design beyond the natural amino acids—0
Self-Organizing Maps of Unbiased Ligand-Target Binding Pathways and Kinetics—0
Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug DesignCode1
GFlowNet Pretraining with Inexpensive Rewards—0
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