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Chemistry Techniques, Synthetic

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Exploring BERT for Reaction Yield Prediction: Evaluating the Impact of Tokenization, Molecular Representation, and Pretraining Data Augmentation.

Journal of chemical information and modeling
Predicting reaction yields in synthetic chemistry remains a significant challenge. This study systematically evaluates the impact of tokenization, molecular representation, pretraining data, and adversarial training on a BERT-based model for yield pr...

Chemistry-informed molecular graph as reaction descriptor for machine-learned retrosynthesis planning.

Proceedings of the National Academy of Sciences of the United States of America
Infusing "chemical wisdom" should improve the data-driven approaches that rely exclusively on historical synthetic data for automatic retrosynthesis planning. For this purpose, we designed a chemistry-informed molecular graph (CIMG) to describe chemi...

Merging enzymatic and synthetic chemistry with computational synthesis planning.

Nature communications
Synthesis planning programs trained on chemical reaction data can design efficient routes to new molecules of interest, but are limited in their ability to leverage rare chemical transformations. This challenge is acute for enzymatic reactions, which...

Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit.

Journal of chemical information and modeling
Machine learning models are increasingly being utilized to predict outcomes of organic chemical reactions. A large amount of reaction data is used to train these models, which is in stark contrast to how expert chemists discover and develop new react...

Computational prediction of complex cationic rearrangement outcomes.

Nature
Recent years have seen revived interest in computer-assisted organic synthesis. The use of reaction- and neural-network algorithms that can plan multistep synthetic pathways have revolutionized this field, including examples leading to advanced natur...

RLSynC: Offline-Online Reinforcement Learning for Synthon Completion.

Journal of chemical information and modeling
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 reverse logic of synthesis reactions, first predict the reaction centers...

Autonomous mobile robots for exploratory synthetic chemistry.

Nature
Autonomous laboratories can accelerate discoveries in chemical synthesis, but this requires automated measurements coupled with reliable decision-making. Most autonomous laboratories involve bespoke automated equipment, and reaction outcomes are ofte...

Chemoenzymatic Synthesis Planning Guided by Reaction Type Score.

Journal of chemical information and modeling
Thanks to the growing interest in computer-aided synthesis planning (CASP), a wide variety of retrosynthesis and retrobiosynthesis tools have been developed in the past decades. However, synthesis planning tools for multistep chemoenzymatic reactions...

Investigations into the Efficiency of Computer-Aided Synthesis Planning.

Journal of chemical information and modeling
The efficiency of machine learning (ML) models is crucial to minimize inference times and reduce the carbon footprints of models deployed in production environments. Current models employed in retrosynthesis to generate a synthesis route from a targe...