Automated synthesis planning has recently re-emerged as a research area at the
intersection of chemistry and machine learning. Despite the appearance of steady progress …

Computer-aided synthesis planning (CASP) aims to automatically learn organic reactivity
from literature and perform retrosynthesis of unseen molecules. CASP systems must learn …

Single-step retrosynthesis aims to predict a set of reactions that lead to the creation of a
target molecule, which is a crucial task in molecular discovery. Although a target molecule …

Planning and conducting chemical syntheses remains a major bottleneck in the discovery of
functional small molecules, and prevents fully leveraging generative AI for molecular inverse …

Abstract Machine learning-assisted retrosynthesis prediction models have been gaining
widespread adoption, though their performances oftentimes degrade significantly when …

Retrosynthesis is an important problem in chemistry and represents an interesting challenge
for AI since it involves predictions over sets of complex, molecular graph structures …

Retrosynthesis, of which the goal is to find a set of reactants for synthesizing a target
product, is an emerging research area of deep learning. While the existing approaches have …

The proper application of retrosynthesis to identify possible transformations for a given target
compound requires a lot of chemistry knowledge and experience. However, because the …

Integrating enzymatic reactions into computer-aided synthesis planning (CASP) should help
devise more selective, economical, and greener synthetic routes. Herein we report the triple …

Retrosynthesis is the process of determining the set of reactant molecules that can react to
form a desired product. Semitemplate-based retrosynthesis methods, which imitate the …