Papers 3D Molecule Generation
“3D Molecule Generation” 태그가 달린 논문 37편 · 필터 해제
Bures-Wasserstein Flow Matching for Graph Generation
Graph generation has emerged as a critical task in fields ranging from molecule design to drug discovery. Contemporary approaches, notably diffusion and flow-based models, have achieved solid graph generative performance…
3D Molecule GenerationDrug DiscoveryGraph GenerationScalable Non-Equivariant 3D Molecule Generation via Rotational Alignment
Equivariant diffusion models have achieved impressive performance in 3D molecule generation. These models incorporate Euclidean symmetries of 3D molecules by utilizing an SE(3)-equivariant denoising network. However, spe…
3D Molecule GenerationDenoisingApplications of Modular Co-Design for De Novo 3D Molecule Generation
De novo 3D molecule generation is a pivotal task in drug discovery. However, many recent geometric generative models struggle to produce high-quality 3D structures, even if they maintain 2D validity and topological stabi…
3D Molecule GenerationDenoisingDrug DiscoveryvalidScalable Autoregressive 3D Molecule Generation
Generative models of 3D molecular structure play a rapidly growing role in the design and simulation of molecules. Diffusion models currently dominate the space of 3D molecule generation, while autoregressive models have…
3D Molecule GenerationGEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation
Deep generative models have shown significant promise in generating valid 3D molecular structures, with the GEOM-Drugs dataset serving as a key benchmark. However, current evaluation protocols suffer from critical flaws,…
3D Molecule GenerationBenchmarkingvalidTowards Unified Latent Space for 3D Molecular Latent Diffusion Modeling
3D molecule generation is crucial for drug discovery and material science, requiring models to process complex multi-modalities, including atom types, chemical bonds, and 3D coordinates. A key challenge is integrating th…
3D Molecule GenerationDrug DiscoveryInductive BiasStraight-Line Diffusion Model for Efficient 3D Molecular Generation
Diffusion-based models have shown great promise in molecular generation but often require a large number of sampling steps to generate valid samples. In this paper, we introduce a novel Straight-Line Diffusion Model (SLD…
3D Molecule GenerationImage GenerationvalidReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation
Protein backbone generation plays a central role in de novo protein design and is significant for many biological and medical applications. Although diffusion and flow-based generative models provide potential solutions …
3D Molecule GenerationProtein DesignProtein FoldingNExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
3D molecule generation is crucial for drug discovery and material design. While prior efforts focus on 3D diffusion models for their benefits in modeling continuous 3D conformers, they overlook the advantages of 1D SELFI…
3D Generation3D Molecule GenerationDrug DiscoveryLanguage Modeling+2BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation
Structure-based drug design (SBDD) leverages the 3D structure of biomolecular targets to guide the creation of new therapeutic agents. Recent advances in generative models, including diffusion models and geometric deep l…
3D Molecule GenerationDrug DesignDrug DiscoveryScore-based 3D molecule generation with neural fields
We introduce a new representation for 3D molecules based on their continuous atomic density fields. Using this representation, we propose a new model based on walk-jump sampling for unconditional 3D molecule generation i…
3D Molecule GenerationD3MES: Diffusion Transformer with multihead equivariant self-attention for 3D molecule generation
Understanding and predicting the diverse conformational states of molecules is crucial for advancing fields such as chemistry, material science, and drug development. Despite significant progress in generative models, ac…
3D Molecule GenerationLearning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation
We consider the conditional generation of 3D drug-like molecules with \textit{explicit control} over molecular properties such as drug-like properties (e.g., Quantitative Estimate of Druglikeness or Synthetic Accessibili…
3D Molecule GenerationDrug DiscoveryLMDM:Latent Molecular Diffusion Model For 3D Molecule Generation
n this work, we propose a latent molecular diffusion model that can make the generated 3D molecules rich in diversity and maintain rich geometric features. The model captures the information of the forces and local const…
3D Molecule GenerationDiversitymodelText-guided Diffusion Model for 3D Molecule Generation
The de novo generation of molecules with targeted properties is crucial in biology, chemistry, and drug discovery. Current generative models are limited to using single property values as conditions, struggling with comp…
3D Molecule GenerationDiversityDrug DiscoverymodelCovariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation
Diffusion models have demonstrated great potential in generating high-quality content for images, natural language, protein domains, etc. However, how to perform user-preferred targeted generation via diffusion models wi…
3D Molecule GenerationBInD: Bond and Interaction-generating Diffusion Model for Multi-objective Structure-based Drug Design
A remarkable advance in geometric deep generative models with accumulated structural data enables structure-based drug design (SBDD) with target protein information only. However, most existing models struggle to address…
3D Molecule GenerationDrug DesignDrug DiscoveryFast 3D Molecule Generation via Unified Geometric Optimal Transport
This paper proposes a new 3D molecule generation framework, called GOAT, for fast and effective 3D molecule generation based on the flow-matching optimal transport objective. Specifically, we formulate a geometric transp…
3D Molecule GenerationMixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation
Deep generative models that produce novel molecular structures have the potential to facilitate chemical discovery. Diffusion models currently achieve state of the art performance for 3D molecule generation. In this work…
3D Molecule GenerationControlMol: Adding Substructure Control To Molecule Diffusion Models
Due to the vast design space of molecules, generating molecules conditioned on a specific sub-structure relevant to a particular function or therapeutic target is a crucial task in computer-aided drug design. Existing wo…
3D Molecule GenerationDrug Designvalid