Chemical Reactivity Mapping: Exploring Chemical Reaction based on Digitalization of Small Molecules through Mayr’s Parameter
Abstract
A new strategy for exploring novel reactions, utilizing Mayr’s reactivity parameters, is developed. We create a highly accurate prediction model of reactivity parameters using machine learning. Validating the reactivity scales in the reactions of isoquinoline and predicting the reactivity in commercially available chemicals lead to a new approach for exploring chemical reactions. Incorporating Mayr's reactivity parameters in both chemical reactivity mapping and chemical reaction space contributes to expedite the exploitation of reactions in small molecule syntheses.
Fields of Study & Subjects
Machine Learning in Materials Science
Computational Drug Discovery Methods
Physical Organic Chemistry and Reaction Kinetics
Publication details
- Journal / source
- ChemRxiv
- Publication date
- 4 March 2026
- Language
- EN
- Document type
- Preprint