Prospective de novo drug design with deep interactome learning

K Atz, L Cotos, C Isert, M Håkansson, D Focht… - Nature …, 2024 - nature.com
De novo drug design aims to generate molecules from scratch that possess specific
chemical and pharmacological properties. We present a computational approach utilizing …

Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry

K Atz, DF Nippa, AT Müller, V Jost, A Anelli… - RSC Medicinal …, 2024 - pubs.rsc.org
Suzuki cross-coupling reactions are considered a valuable tool for constructing carbon–
carbon bonds in small molecule drug discovery. However, the synthesis of chemical matter …

Exploring protein–ligand binding affinity prediction with electron density-based geometric deep learning

C Isert, K Atz, S Riniker, G Schneider - RSC advances, 2024 - pubs.rsc.org
Rational structure-based drug design relies on accurate predictions of protein–ligand
binding affinity from structural molecular information. Although deep learning-based …

Simple User-Friendly Reaction Format

DF Nippa, AT Müller, K Atz, DB Konrad, U Grether… - 2024 - chemrxiv.org
Leveraging the increasing volume of chemical reaction data can enhance synthesis
planning and improve suc-cess rates. However, machine learning applications for …