Papers Drug Design
“Drug Design” 태그가 달린 논문 440편 · 필터 해제
Assay2Mol: large language model-based drug design using BioAssay context
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate the functional responses of candidate molecules against disease targets. Un…
DescriptiveDrug DesignDrug DiscoveryIn-Context Learning+3TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality
State-of-the-art models for 3D molecular generation are based on significant inductive biases, SE(3), permutation equivariance to respect symmetry and graph message-passing networks to capture local chemistry, yet the ge…
Drug DesignCovDocker: Benchmarking Covalent Drug Design with Tasks, Datasets, and Solutions
Molecular docking plays a crucial role in predicting the binding mode of ligands to target proteins, and covalent interactions, which involve the formation of a covalent bond between the ligand and the target, are partic…
BenchmarkingDrug DesignMolecular DockingDiverse Mini-Batch Selection in Reinforcement Learning for Efficient Chemical Exploration in de novo Drug Design
In many real-world applications, evaluating the goodness of instances is often costly and time-consuming, e.g., human feedback and physics simulations, in contrast to proposing new instances. In particular, this is even …
Drug DesignDrug DiscoveryPoint ProcessesActive Learning-Guided Seq2Seq Variational Autoencoder for Multi-target Inhibitor Generation
Simultaneously optimizing molecules against multiple therapeutic targets remains a profound challenge in drug discovery, particularly due to sparse rewards and conflicting design constraints. We propose a structured acti…
Active LearningDiversityDrug DesignDrug DiscoveryReimagining Target-Aware Molecular Generation through Retrieval-Enhanced Aligned Diffusion
Breakthroughs in high-accuracy protein structure prediction, such as AlphaFold, have established receptor-based molecule design as a critical driver for rapid early-phase drug discovery. However, most approaches still st…
Drug DesignDrug DiscoveryProtein Structure PredictionRetrieval+2Scalable and Cost-Efficient de Novo Template-Based Molecular Generation
Template-based molecular generation offers a promising avenue for drug design by ensuring generated compounds are synthetically accessible through predefined reaction templates and building blocks. In this work, we tackl…
DiversityDrug DesignUniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection
The detection of ligand binding sites for proteins is a fundamental step in Structure-Based Drug Design. Despite notable advances in recent years, existing methods, datasets, and evaluation metrics are confronted with se…
Drug DesignPredictionBridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation
Hybrid quantum-classical machine learning offers a path to leverage noisy intermediate-scale quantum (NISQ) devices for drug discovery, but optimal model architectures remain unclear. We systematically optimize the quant…
Bayesian OptimizationDrug DesignDrug DiscoveryLarge Language Models for Controllable Multi-property Multi-objective Molecule Optimization
In real-world drug design, molecule optimization requires selectively improving multiple molecular properties up to pharmaceutically relevant levels, while maintaining others that already meet such criteria. However, exi…
Drug DesignA Graph Completion Method that Jointly Predicts Geometry and Topology Enables Effective Molecule Assembly
A common starting point for drug design is to find small chemical groups or "fragments" that form interactions with distinct subregions in a protein binding pocket. The subsequent challenge is to assemble these fragments…
DenoisingDrug DesignDrug DiscoveryScene UnderstandingBeyond Chemical QA: Evaluating LLM's Chemical Reasoning with Modular Chemical Operations
While large language models (LLMs) with Chain-of-Thought (CoT) reasoning excel in mathematics and coding, their potential for systematic reasoning in chemistry, a domain demanding rigorous structural analysis for real-wo…
Chemical Reaction PredictionDrug DesignMathematical ProofsTemplate-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization
Predicting the 3D conformation of small molecules within protein binding sites is a key challenge in drug design. When a crystallized reference ligand (template) is available, it provides geometric priors that can guide …
Drug DesignPose PredictionEvolutionary training-free guidance in diffusion model for 3D multi-objective molecular generation
Discovering novel 3D molecular structures that simultaneously satisfy multiple property targets remains a central challenge in materials and drug design. Although recent diffusion-based models can generate 3D conformatio…
DenoisingDrug DesignPharmacophore-Conditioned Diffusion Model for Ligand-Based De Novo Drug Design
Developing bioactive molecules remains a central, time- and cost-heavy challenge in drug discovery, particularly for novel targets lacking structural or functional data. Pharmacophore modeling presents an alternative for…
Drug DesignDrug DiscoveryPiloting Structure-Based Drug Design via Modality-Specific Optimal Schedule
Structure-Based Drug Design (SBDD) is crucial for identifying bioactive molecules. Recent deep generative models are faced with challenges in geometric structure modeling. A major bottleneck lies in the twisted probabili…
Drug DesignSchedulingA 3D pocket-aware and evolutionary conserved interaction guided diffusion model for molecular optimization
Generating molecules that bind to specific protein targets via diffusion models has shown good promise for structure-based drug design and molecule optimization. Especially, the diffusion models with binding interaction …
Drug DesignEnhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning
Chemical reaction and retrosynthesis prediction are fundamental tasks in drug discovery. Recently, large language models (LLMs) have shown potential in many domains. However, directly applying LLMs to these tasks faces t…
Drug DesignDrug DiscoveryLanguage ModelingLanguage Modelling+3Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks
SMILES-based molecule generation has emerged as a powerful approach in drug discovery. Deep reinforcement learning (RL) using large language model (LLM) has been incorporated into the molecule generation process to achie…
Deep Reinforcement LearningDrug DesignDrug DiscoveryLarge Language Model+1Combining GCN Structural Learning with LLM Chemical Knowledge for or Enhanced Virtual Screening
Virtual screening plays a critical role in modern drug discovery by enabling the identification of promising candidate molecules for experimental validation. Traditional machine learning methods such as support vector ma…
Computational EfficiencyDrug DesignDrug Discovery