Retrosynthesis
51 papers with code • 1 benchmarks • 1 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.
Most implemented papers
Learning Graph Models for Retrosynthesis Prediction
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.
Computer-Assisted Retrosynthesis Based on Molecular Similarity
We demonstrate molecular similarity to be a surprisingly effective metric for proposing and ranking one-step retrosynthetic disconnections based on analogy to precedent reactions.
A Model to Search for Synthesizable Molecules
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
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
Retrosynthesis is the process of recursively decomposing target molecules into available building blocks.
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction
Finding synthesis routes for molecules of interest is an essential step in the discovery of new drugs and materials.