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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

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Showing 1–50 of 110 papers

TitleStatusHype
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis ConstraintsCode2
Chemformer: a pre-trained transformer for computational chemistryCode2
RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNetsCode2
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task TuningCode2
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional SearchCode1
Predictive Chemistry Augmented with Text RetrievalCode1
Leveraging Large Language Models as Knowledge-Driven Agents for Reliable Retrosynthesis PlanningCode1
RetroXpert: Decompose Retrosynthesis Prediction like a ChemistCode1
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text PretrainingCode1
Deep Retrosynthetic Reaction Prediction using Local Reactivity and Global AttentionCode1
Leveraging Reaction-aware Substructures for Retrosynthesis AnalysisCode1
Dual-view Molecule Pre-trainingCode1
Retroformer: Pushing the Limits of Interpretable End-to-end Retrosynthesis TransformerCode1
UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES AlignmentCode1
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph EditsCode1
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesisCode1
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent VariablesCode1
A Model to Search for Synthesizable MoleculesCode1
O-GNN: Incorporating Ring Priors into Molecular ModelingCode1
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction predictionCode1
Root-aligned SMILES: A Tight Representation for Chemical Reaction PredictionCode1
RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictionsCode1
Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert KnowledgeCode1
RetroBridge: Modeling Retrosynthesis with Markov BridgesCode1
DirectMultiStep: Direct Route Generation for Multi-Step RetrosynthesisCode1
Re-evaluating Retrosynthesis Algorithms with SyntheseusCode1
MechRetro is a chemical-mechanism-driven graph learning framework for interpretable retrosynthesis prediction and pathway planningCode1
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain FeedbackCode1
Retro-fallback: retrosynthetic planning in an uncertain worldCode1
Motif-based Graph Self-Supervised Learning for Molecular Property PredictionCode1
Retrosynthesis Prediction with Conditional Graph Logic NetworkCode1
A Bayesian algorithm for retrosynthesisCode1
GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion GenerationCode1
Retrosynthetic Planning with Dual Value NetworksCode1
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic PlanningCode1
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template PredictionCode1
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug DiscoveryCode1
Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield NetworksCode1
Learning Graph Models for Retrosynthesis PredictionCode1
Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step RetrosynthesisCode1
MotifRetro: Exploring the Combinability-Consistency Trade-offs in retrosynthesis via Dynamic Motif EditingCode1
G^2Retro as a Two-Step Graph Generative Models for Retrosynthesis PredictionCode1
Directly Optimizing for Synthesizability in Generative Molecular Design using Retrosynthesis ModelsCode0
DiffER: Categorical Diffusion for Chemical RetrosynthesisCode0
A Self-feedback Knowledge Elicitation Approach for Chemical Reaction PredictionsCode0
Retro-BLEU: Quantifying Chemical Plausibility of Retrosynthesis Routes through Reaction Template Sequence AnalysisCode0
RetroComposer: Composing Templates for Template-Based Retrosynthesis PredictionCode0
Leveraging Large Language Models for enzymatic reaction prediction and characterizationCode0
Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural NetworksCode0
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