Limited Proteolysis (LiP)

Understanding the target of a small molecule compound is key to gaining deeper insight into its mechanism of action and potential toxicities.

The Limited Proteolysis technology coupled to next-generation quantitative mass spectrometry (LiP-MS) is a novel approach that enables the unbiased profiling of structural protein changes across the whole proteome. Structural changes to the proteome can result from a variety of stimuli such as heat shock, protein-protein interactions, compound binding, and posttranslational modifications. The structural changes affect the kinetics of the proteolytic cleavage in the LiP reaction and can be probed using next-generation quantitative proteomics approaches such as HRM.


LiP-MS for Target Deconvolution

LiP-MS has emerged as a label-free technology to identify and analyze changes in protein structures/steric hindrance caused by compound binding in cellular lysates. The underlying concept of LiP-MS is based on proteins being subjected to proteolysis in the presence or absence of a compound. When a compound binds to a protein, it induces a specific structural state in the protein target that can be exploited during proteolysis. This unique structural state changes the pattern of proteolysis and leads to the formation of unique peptides that can be characterized by HRM mass spectrometry.


Check out this video for a detailed explanation on the mechanisms of action of LiP-MS:

Developed by the group of Prof. Paola Picotti at ETH Zurich, LiP-MS is a patented technology (WO2014082733 A1) and is exclusively licensed to Biognosys.

Biognosys has developed machine-learning-based applications of the LiP-MS technology for the identification of small molecule binding sites, drug target deconvolution, and proteome-wide discovery of induced structural changes. Biognosys offers the technology as contract research services.

For more information click here.  


«The LiP technology is a very valuable tool to identify target and off-target of novel compounds whatever the organism and to support the process of target deconvolution in research. The interactions with Biognosys are very nice and fruitful. The team is engaged and responsive throughout the project.»

Thomas Knoblauch
Laboratory Manager, Bayer



Recent Publications

A Machine Learning-based Chemoproteomic Approach to Identify Drug Targets and Binding Sites in Complex Proteomes”, Nature Communications, 2020

"A Map of Protein-Metabolite Interactions Reveals Principles of Chemical Communication", Cell, 2018

Cell-wide Analysis of Protein Thermal Unfolding Reveals Determinants of Thermostability”, Science, 2017

Global Analysis of Protein Structural Changes in Complex Proteomes”, Nature Biotechnology, 2014


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