Work

Molecular field analysis for data-driven molecular design in asymmetric catalysis

Year: 2022

Type: article

Abstract: This review highlights the recent advances (2019-present) in the use of MFA (molecular field analysis) for data-driven catalyst design, enabling to improve selectivities/reaction outcomes in asymmetric catalysis. Successful examples of MFA-based molecular design and how to design molecules by MFA are described, including how to generate and evaluate MFA-based regression models, and future challenges in MFA-based molecular design in molecular catalysis.

Source: Organic & Biomolecular Chemistry

DOI: 10.1039/d2ob00228k

Author: Shigeru Yamaguchi

Institution: RIKEN Center for Sustainable Resource Science

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Japan Society for the Promotion of Science, RIKEN

Award: G237906249