Image de couverture de livre

Efficient and Programmable Exploration of Synthesizable Chemical Space

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Luo, Shitong, Coley, Connor W.
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Biomolecules
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Generative Artificial Intelligence for Navigating Synthesizable Chemical Space
par: Gao, Wenhao, et autres
Publié: (2024)

Procedural Synthesis of Synthesizable Molecules
par: Sun, Michael, et autres
Publié: (2024)

ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design
par: Adams, Keir, et autres
Publié: (2024)

Generative Molecular Design with Steerable and Granular Synthesizability Control
par: Guo, Jeff, et autres
Publié: (2025)

Quantum-inspired Reinforcement Learning for Synthesizable Drug Design
par: Wang, Dannong, et autres
Publié: (2024)

Revealing the Relationship Between Publication Bias and Chemical Reactivity with Contrastive Learning
par: Gao, Wenhao, et autres
Publié: (2024)

It Takes Two to Tango: Directly Optimizing for Constrained Synthesizability in Generative Molecular Design
par: Guo, Jeff, et autres
Publié: (2024)

Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
par: Peng, Xingang, et autres
Publié: (2022)

Effective Protein-Protein Interaction Exploration with PPIretrieval
par: Hua, Chenqing, et autres
Publié: (2024)

RGFN: Synthesizable Molecular Generation Using GFlowNets
par: Koziarski, Michał, et autres
Publié: (2024)

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
par: Xu, Minkai, et autres
Publié: (2021)

ChemSpaceAL: An Efficient Active Learning Methodology Applied to Protein-Specific Molecular Generation
par: Kyro, Gregory W., et autres
Publié: (2023)

A Collaborative Framework Integrating Large Language Model and Chemical Fragment Space: Mutual Inspiration for Lead Design
par: Tuo, Hao, et autres
Publié: (2025)

Full-Atom Peptide Design based on Multi-modal Flow Matching
par: Li, Jiahan, et autres
Publié: (2024)

Orientation-Aware Graph Neural Networks for Protein Structure Representation Learning
par: Li, Jiahan, et autres
Publié: (2022)

Conditional Chemical Language Models are Versatile Tools in Drug Discovery
par: Zhu, Lu, et autres
Publié: (2025)

A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Prediction
par: Özçelik, Rıza, et autres
Publié: (2024)

Directed Evolution of Proteins via Bayesian Optimization in Embedding Space
par: Soldát, Matouš, et autres
Publié: (2025)

Atomic Trajectory Modeling with State Space Models for Biomolecular Dynamics
par: Shi, Liang, et autres
Publié: (2026)

Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension
par: Li, Jiahan, et autres
Publié: (2024)

Multi-Objective Latent Space Optimization of Generative Molecular Design Models
par: Abeer, A N M Nafiz, et autres
Publié: (2022)

Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
par: Ketata, Mohamed Amine, et autres
Publié: (2024)

MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
par: Qu, Yanru, et autres
Publié: (2024)

Bridging the Gap between Chemical Reaction Pretraining and Conditional Molecule Generation with a Unified Model
par: Qiang, Bo, et autres
Publié: (2023)

Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
par: Lu, Shuqi, et autres
Publié: (2025)

Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding
par: Zhong, Zhiqiang, et autres
Publié: (2024)

Towards Efficient Molecular Property Optimization with Graph Energy Based Models
par: Miglior, Luca, et autres
Publié: (2025)

Latent Chemical Space Searching for Plug-in Multi-objective Molecule Generation
par: Liu, Ningfeng, et autres
Publié: (2024)

Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design
par: Guo, Jeff, et autres
Publié: (2023)

Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering
par: Jiao, Shujian, et autres
Publié: (2024)

DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
par: Yan, Jiaxian, et autres
Publié: (2024)

Accurate and Efficient Structural Ensemble Generation of Macrocyclic Peptides using Internal Coordinate Diffusion
par: Grambow, Colin A., et autres
Publié: (2023)

PharMolixFM: All-Atom Foundation Models for Molecular Modeling and Generation
par: Luo, Yizhen, et autres
Publié: (2025)

Graph Diffusion Transformers for Multi-Conditional Molecular Generation
par: Liu, Gang, et autres
Publié: (2024)

NEBULA: Neural Empirical Bayes Under Latent Representations for Efficient and Controllable Design of Molecular Libraries
par: Nowara, Ewa M., et autres
Publié: (2024)

Energy Efficient Protein Language Models: Leveraging Small Language Models with LoRA for Controllable Protein Generation
par: Shah, Aayush, et autres
Publié: (2024)

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding
par: Wu, Lirong, et autres
Publié: (2024)

A Model-Centric Review of Deep Learning for Protein Design
par: Kyro, Gregory W., et autres
Publié: (2025)

Learning Multi-view Molecular Representations with Structured and Unstructured Knowledge
par: Luo, Yizhen, et autres
Publié: (2024)

Training Dynamics of Learning 3D-Rotational Equivariance
par: Shen, Max W., et autres
Publié: (2025)