Unraveling the mechanism of action and molecular target of small molecules remains a major challenge in drug development. This paper introduces LiP-Quant, a machine learning-based drug target deconvolution pipeline using limited proteolysis coupled with mass spectrometry. LiP-Quant identifies small-molecule targets, predicts binding sites, and estimates binding affinities across diverse compound classes and species, including human cells. Its effectiveness is demonstrated through target identification for various drugs and the discovery of a novel fungicide target.
Publisher
Nature Communications
Published On
Aug 21, 2020
Authors
Ilaria Piazza, Nigel Beaton, Roland Bruderer, Thomas Knobloch, Crystel Barbisan, Lucie Chandat, Alexander Sudau, Isabella Siepe, Oliver Rinner, Natalie de Souza, Paola Picotti, Lukas Reiter
Tags
machine learning
drug development
mass spectrometry
target identification
binding affinities
small molecules
limited proteolysis
Related Publications
Explore these studies to deepen your understanding of the subject.
