FRAGMENTA: Efficient End-to-end Fragmentation-based Generative Model with Agentic Tuning for Drug Lead Optimization in Small Data Regime
cs.AI
Submitted: 2025-11-25
Updated: 2026-10-06
Terminology
Sources
- ChemCrow: Augmenting large-language models with chemistry tools
- Generative Artificial Intelligence for Navigating Synthesizable Chemical Space
- Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
- De Novo Molecular Generation via Connection-aware Motif Mining
- Data-Efficient Graph Grammar Learning for Molecular Generation
- Drug Discovery with Dynamic Goal-aware Fragments
- Generating 3D Molecules for Target Protein Binding
- GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
- Learning to Extend Molecular Scaffolds with Structural Motifs
- MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
- Symmetry-Aware Actor-Critic for 3D Molecular Design
- POLO: Preference-Guided Multi-Turn Reinforcement Learning for Lead Optimization
- GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation
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