Machine learning in chemical reaction space.

ABSTRACT: Chemical compound space refers to the vast set of all possible chemical compounds, estimated to contain 10⁶⁰ molecules. While intractable as a whole, modern machine learning (ML) is increasingly capable of accurately predicting molecular properties in important subsets. Here, we therefore engage in the ML-driven study of even larger reaction space. Central to chemistry as a science of transformations, this space contains all possible chemical reactions. As an important basis for 'reactive' ML, we establish a first-principles database (Rad-6) containing closed and open-shell organic molecules, along with an associated database of chemical reaction energies (Rad-6-RE). We show that the special topology of reaction spaces, with central hub molecules involved in multiple reactions,

SUBMITTER: Stocker S 

PROVIDER: S-EPMC7603480 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature