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Lookup NU author(s): Amy George,
Dr Jessica Watt,
Dr Mathew Martin,
Professor Matthias TrostORCiD,
Dr Jose Luis Marin-RubioORCiD,
Dr Maria Duenas FadicORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2023 The Authors. Published by American Chemical SocietyThermal proteome profiling (TPP) provides a powerful approach to studying proteome-wide interactions of small therapeutic molecules and their target and off-target proteins, complementing phenotypic-based drug screens. Detecting differences in thermal stability due to target engagement requires high quantitative accuracy and consistent detection. Isobaric tandem mass tags (TMTs) are used to multiplex samples and increase quantification precision in TPP analysis by data-dependent acquisition (DDA). However, advances in data-independent acquisition (DIA) can provide higher sensitivity and protein coverage with reduced costs and sample preparation steps. Herein, we explored the performance of different DIA-based label-free quantification approaches compared to TMT-DDA for thermal shift quantitation. Acute myeloid leukemia cells were treated with losmapimod, a known inhibitor of MAPK14 (p38α). Label-free DIA approaches, and particularly the library-free mode in DIA-NN, were comparable of TMT-DDA in their ability to detect target engagement of losmapimod with MAPK14 and one of its downstream targets, MAPKAPK3. Using DIA for thermal shift quantitation is a cost-effective alternative to labeled quantitation in the TPP pipeline.
Author(s): George AL, Sidgwick FR, Watt JE, Martin MP, Trost M, Marin-Rubio JL, Duenas ME
Publication type: Article
Publication status: Published
Journal: Journal of Proteome Research
Print publication date: 04/08/2023
Online publication date: 13/07/2023
Acceptance date: 17/02/2023
Date deposited: 08/09/2023
ISSN (print): 1535-3893
ISSN (electronic): 1535-3907
Publisher: American Chemical Society
Data Access Statement: The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier: PXD040173.
PubMed id: 37439223
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