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Retrosynthesis

Retrosynthetic analysis is a pivotal synthetic methodology in organic chemistry that employs a reverse-engineering approach, initiating from the target compound and retroactively tracing potential synthesis routes and precursor molecules. This technique proves instrumental in sculpting efficient synthetic strategies for intricate molecules, thus catalyzing the evolution and progression of novel pharmaceuticals and materials.

Papers

Showing 125 of 110 papers

TitleStatusHype
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis ConstraintsCode2
Chemformer: a pre-trained transformer for computational chemistryCode2
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task TuningCode2
RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNetsCode2
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain FeedbackCode1
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph EditsCode1
Motif-based Graph Self-Supervised Learning for Molecular Property PredictionCode1
MechRetro is a chemical-mechanism-driven graph learning framework for interpretable retrosynthesis prediction and pathway planningCode1
Leveraging Large Language Models as Knowledge-Driven Agents for Reliable Retrosynthesis PlanningCode1
Dual-view Molecule Pre-trainingCode1
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template PredictionCode1
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic PlanningCode1
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug DiscoveryCode1
A Bayesian algorithm for retrosynthesisCode1
DirectMultiStep: Direct Route Generation for Multi-Step RetrosynthesisCode1
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesisCode1
GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion GenerationCode1
A Model to Search for Synthesizable MoleculesCode1
Learning Graph Models for Retrosynthesis PredictionCode1
Leveraging Reaction-aware Substructures for Retrosynthesis AnalysisCode1
G^2Retro as a Two-Step Graph Generative Models for Retrosynthesis PredictionCode1
Deep Retrosynthetic Reaction Prediction using Local Reactivity and Global AttentionCode1
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional SearchCode1
Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield NetworksCode1
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