Goetz, J., Jackl, M. K., Jindakun, C., Marziale, A. N., Andre, Jerome, Gosling, Daniel, Springer, C., Palmieri, Marco, Reck, Marcel, Luneau, Alexandre, Brocklehurst, Cara and Bode, J. W. (2023) High-throughput synthesis provides data for predicting molecular properties and reaction success. Science advances, 9 (43). eadj2314. ISSN 2375-2548

Abstract

The generation of attractive scaffolds for drug discovery efforts requires the expeditious synthesis of diverse analogues from readily available building blocks. This endeavor necessitates a trade-off between diversity and ease of access and is further complicated by uncertainty about the synthesizability and pharmacokinetic properties of the resulting compounds. Here, we document a platform that leverages photocatalytic N-heterocycle synthesis, high-throughput experimentation, automated purification, and physicochemical assays on 1152 discrete reactions. Together, the data generated allow rational predictions of the synthesizability of stereochemically diverse C-substituted N-saturated heterocycles with deep learning and reveal unexpected trends on the relationship between structure and properties. This study exemplifies how organic chemists can exploit state-of-the-art technologies to markedly increase throughput and confidence in the preparation of drug-like molecules.

Item Type:	Article
Keywords:	Drug Discovery Pharmacokinetics High-Throughput Screening Assays Chemistry Techniques, Synthetic
Date Deposited:	30 Dec 2023 00:45
Last Modified:	30 Dec 2023 00:45
URI:	https://oak.novartis.com/id/eprint/50710