Cover Image

ControlMol: Adding Substructure Control To Molecule Diffusion Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhengyang, Qi, Zijing, Liu, Jiying, Zhang, He, Cao, Yu, Li
Format:	Preprint
Published:	2024
Subjects:	Biomolecules Artificial Intelligence Machine Learning Chemical Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Text-guided Diffusion Model for 3D Molecule Generation
by: Luo, Yanchen, et al.
Published: (2024)

Mol-LLM: Multimodal Generalist Molecular LLM with Improved Graph Utilization
by: Lee, Chanhui, et al.
Published: (2025)

Unified Generative Modeling of 3D Molecules via Bayesian Flow Networks
by: Song, Yuxuan, et al.
Published: (2024)

InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery
by: Cao, He, et al.
Published: (2023)

Sculpting Molecules in Text-3D Space: A Flexible Substructure Aware Framework for Text-Oriented Molecular Optimization
by: Zhang, Kaiwei, et al.
Published: (2024)

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge
by: Huang, Yufei, et al.
Published: (2024)

Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation
by: Park, Jiwoong, et al.
Published: (2024)

Diffusion-Driven Generative Framework for Molecular Conformation Prediction
by: Yang, Bobin, et al.
Published: (2023)

A Novel 4-D Dataset Paradigm for Studying Complete Ligand-Protein Dissociation Dynamics
by: Li, Maodong, et al.
Published: (2025)

Pre-trained Molecular Language Models with Random Functional Group Masking
by: Peng, Tianhao, et al.
Published: (2024)

MultiModal-Learning for Predicting Molecular Properties: A Framework Based on Image and Graph Structures
by: Wang, Zhuoyuan, et al.
Published: (2023)

Tokenization for Molecular Foundation Models
by: Wadell, Alexius, et al.
Published: (2024)

Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning
by: Torren-Peraire, Paula, et al.
Published: (2023)

General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design
by: Jian, Yue, et al.
Published: (2024)

ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language Models
by: Huang, Yuqing, et al.
Published: (2024)

Multi-objective fluorescent molecule design with a data-physics dual-driven generative framework
by: Li, Yanheng, et al.
Published: (2026)

ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha
by: Liu, Meng, et al.
Published: (2025)

Revealing the Relationship Between Publication Bias and Chemical Reactivity with Contrastive Learning
by: Gao, Wenhao, et al.
Published: (2024)

REBIND: Enhancing ground-state molecular conformation via force-based graph rewiring
by: Kim, Taewon, et al.
Published: (2024)

Generative Artificial Intelligence for Navigating Synthesizable Chemical Space
by: Gao, Wenhao, et al.
Published: (2024)

WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction
by: Wang, Fanmeng, et al.
Published: (2024)

Superior Molecular Representations from Intermediate Encoder Layers
by: Pinto, Luis
Published: (2025)

Two-Stage Pretraining for Molecular Property Prediction in the Wild
by: Wijaya, Kevin Tirta, et al.
Published: (2024)

GraphBPE: Molecular Graphs Meet Byte-Pair Encoding
by: Shen, Yuchen, et al.
Published: (2024)

Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes
by: Hong, Haokai, et al.
Published: (2024)

Molecular Graph Representation Learning Integrating Large Language Models with Domain-specific Small Models
by: Zhang, Tianyu, et al.
Published: (2024)

Procedural Synthesis of Synthesizable Molecules
by: Sun, Michael, et al.
Published: (2024)

Transfer Learning across Different Chemical Domains: Virtual Screening of Organic Materials with Deep Learning Models Pretrained on Small Molecule and Chemical Reaction Data
by: Zhang, Chengwei, et al.
Published: (2023)

LICO: Large Language Models for In-Context Molecular Optimization
by: Nguyen, Tung, et al.
Published: (2024)

Apo2Mol: 3D Molecule Generation via Dynamic Pocket-Aware Diffusion Models
by: Zheng, Xinzhe, et al.
Published: (2025)

ControllableGPT: A Ground-Up Designed Controllable GPT for Molecule Optimization
by: Liu, Xuefeng, et al.
Published: (2025)

Look the Other Way: Designing 'Positive' Molecules with Negative Data via Task Arithmetic
by: Özçelik, Rıza, et al.
Published: (2025)

Training-Free Guidance for Discrete Diffusion Models for Molecular Generation
by: Kerby, Thomas J., et al.
Published: (2024)

Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion Model
by: Xiang, Yuran, et al.
Published: (2024)

Language models in molecular discovery
by: Janakarajan, Nikita, et al.
Published: (2023)

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
by: Zhang, He, et al.
Published: (2024)

Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation
by: Zhang, Odin, et al.
Published: (2024)

Unraveling the Potential of Diffusion Models in Small Molecule Generation
by: Zhang, Peining, et al.
Published: (2025)

Human-level molecular optimization driven by mol-gene evolution
by: Fang, Jiebin, et al.
Published: (2024)

Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
by: Liu, Gang, et al.
Published: (2024)