Retrosynthesis
41 papers with code • 1 benchmarks • 0 datasets
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.
Benchmarks
These leaderboards are used to track progress in Retrosynthesis
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
Most implemented papers
Learning Graph Models for Retrosynthesis Prediction
vsomnath/graphretro
•
•
NeurIPS 2021
Retrosynthesis prediction is a fundamental problem in organic synthesis, where the task is to identify precursor molecules that can be used to synthesize a target molecule.
A Model to Search for Synthesizable Molecules
john-bradshaw/molecule-chef
•
•
NeurIPS 2019
Deep generative models are able to suggest new organic molecules by generating strings, trees, and graphs representing their structure.
Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks
Synthesis planning is the process of recursively decomposing target molecules into available precursors.
Retrosynthesis Prediction with Conditional Graph Logic Network
Hanjun-Dai/GLN
•
•
NeurIPS 2019
Retrosynthesis is one of the fundamental problems in organic chemistry.
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesis
We investigated the effect of different training scenarios on predicting the (retro)synthesis of chemical compounds using a text-like representation of chemical reactions (SMILES) and Natural Language Processing neural network Transformer architecture.
A Bayesian algorithm for retrosynthesis
The identification of synthetic routes that end with a desired product has been an inherently time-consuming process that is largely dependent on expert knowledge regarding a limited fraction of the entire reaction space.
Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits
The central challenge in automated synthesis planning is to be able to generate and predict outcomes of a diverse set of chemical reactions.
RetroXpert: Decompose Retrosynthesis Prediction like a Chemist
uta-smile/RetroXpert
•
•
NeurIPS 2020
Retrosynthesis is the process of recursively decomposing target molecules into available building blocks.
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction
ml-jku/mhn-react
•
•
Finding synthesis routes for molecules of interest is an essential step in the discovery of new drugs and materials.
Dual-view Molecule Pre-training
microsoft/DVMP
•
•
After pre-training, we can use either the Transformer branch (this one is recommended according to empirical results), the GNN branch, or both for downstream tasks.
