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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
RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNetsCode2
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis ConstraintsCode2
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task TuningCode2
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
Chemformer: a pre-trained transformer for computational chemistryCode2
Leveraging Large Language Models as Knowledge-Driven Agents for Reliable Retrosynthesis PlanningCode1
GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion GenerationCode1
Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert KnowledgeCode1
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional SearchCode1
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text PretrainingCode1
DirectMultiStep: Direct Route Generation for Multi-Step RetrosynthesisCode1
UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES AlignmentCode1
Predictive Chemistry Augmented with Text RetrievalCode1
Re-evaluating Retrosynthesis Algorithms with SyntheseusCode1
Retro-fallback: retrosynthetic planning in an uncertain worldCode1
Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step RetrosynthesisCode1
RetroBridge: Modeling Retrosynthesis with Markov BridgesCode1
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain FeedbackCode1
MotifRetro: Exploring the Combinability-Consistency Trade-offs in retrosynthesis via Dynamic Motif EditingCode1
O-GNN: Incorporating Ring Priors into Molecular ModelingCode1
Retrosynthetic Planning with Dual Value NetworksCode1
MechRetro is a chemical-mechanism-driven graph learning framework for interpretable retrosynthesis prediction and pathway planningCode1
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic PlanningCode1
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug DiscoveryCode1
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent VariablesCode1
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