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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 51–100 of 110 papers

TitleStatusHype
ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain FeedbackCode1
MotifRetro: Exploring the Combinability-Consistency Trade-offs in retrosynthesis via Dynamic Motif EditingCode1
G-MATT: Single-step Retrosynthesis Prediction using Molecular Grammar Tree Transformer—0
O-GNN: Incorporating Ring Priors into Molecular ModelingCode1
Deep Learning Methods for Small Molecule Drug Discovery: A Survey—0
Retrosynthetic Planning with Dual Value NetworksCode1
RCsearcher: Reaction Center Identification in Retrosynthesis via Deep Q-Learning—0
Recent advances in artificial intelligence for retrosynthesis—0
Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction—0
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
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction—0
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug DiscoveryCode1
Quantum Machine Learning for Material Synthesis and Hardware Security—0
Modeling Diverse Chemical Reactions for Single-step Retrosynthesis via Discrete Latent VariablesCode1
G^2Retro as a Two-Step Graph Generative Models for Retrosynthesis PredictionCode1
G2GT: Retrosynthesis Prediction with Graph to Graph Attention Neural Network and Self-TrainingCode0
Leveraging Reaction-aware Substructures for Retrosynthesis AnalysisCode1
Root-aligned SMILES: A Tight Representation for Chemical Reaction PredictionCode1
SemiRetro: Semi-template framework boosts deep retrosynthesis prediction—0
Chemformer: a pre-trained transformer for computational chemistryCode2
Retroformer: Pushing the Limits of Interpretable End-to-end Retrosynthesis TransformerCode1
Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield NetworksCode1
RetroComposer: Composing Templates for Template-Based Retrosynthesis PredictionCode0
Towards understanding retrosynthesis by energy-based models—0
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction predictionCode1
Motif-based Graph Self-Supervised Learning for Molecular Property PredictionCode1
Human-in-the-loop for a Disconnection Aware Retrosynthesis—0
RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictionsCode1
ChemiRise: a data-driven retrosynthesis engine—0
Deep Retrosynthetic Reaction Prediction using Local Reactivity and Global AttentionCode1
Dual-view Molecule Pre-trainingCode1
Learning Graph Models for Template-Free Retrosynthesis—0
BioNavi-NP: Biosynthesis Navigator for Natural Products—0
RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning—0
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template PredictionCode1
PolyRetro: Few-shot Polymer Retrosynthesis via Domain Adaptation—0
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design—0
RetroXpert: Decompose Retrosynthesis Prediction like a ChemistCode1
Data Transfer Approaches to Improve Seq-to-Seq Retrosynthesis—0
Energy-based View of Retrosynthesis—0
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph EditsCode1
Learning Graph Models for Retrosynthesis PredictionCode1
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models—0
A Graph to Graphs Framework for Retrosynthesis Prediction—0
A Bayesian algorithm for retrosynthesisCode1
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesisCode1
Retrosynthesis Prediction with Conditional Graph Logic NetworkCode1
Value-Added Chemical Discovery Using Reinforcement Learning—0
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis—0
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