Browse by author
Lookup NU author(s): Professor Matthias TrostORCiD, Dr Maria Duenas FadicORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2022. MALDI-TOF MS is a powerful analytical technique that provides a fast and label-free readout for in vitro assays in the high-throughput screening (HTS) environment. Here, we describe the development of a novel, HTS compatible, MALDI-TOF MS-based drug discovery assay for the endoplasmic reticulum aminopeptidase 1 (ERAP1), an important target in immuno-oncology and auto-immune diseases. A MALDI-TOF MS assay was developed beginning with an already established ERAP1 RapidFire MS (RF MS) assay, where the peptide YTAFTIPSI is trimmed into the product TAFTIPSI. We noted low ionisation efficiency of these peptides in MALDI-TOF MS and hence incorporated arginine residues into the peptide sequences to improve ionisation. The optimal assay conditions were established with these new basic assay peptides on the MALDI-TOF MS platform and validated with known ERAP1 inhibitors. Assay stability, reproducibility and robustness was demonstrated on the MALDI-TOF MS platform. From a set of 699 confirmed ERAP1 binders, identified in a prior affinity selection mass spectrometry (ASMS) screen, active compounds were determined at single concentration and in a dose-response format with the new MALDI-TOF MS setup. Furthermore, to allow for platform performance comparison, the same compound set was tested on the established RF MS setup, as the new basic peptides showed fragmentation in ESI-MS. The two platforms showed a comparable performance, but the MALDI-TOF MS platform had several advantages, such as shorter sample cycle times, reduced reagent consumption, and a lower tight-binding limit.
Author(s): Muller L, Burton AK, Tayler CL, Rowedder JE, Hutchinson JP, Peace S, Quayle JM, Leveridge MV, Annan RS, Trost M, Peltier-Heap RE, Duenas ME
Publication type: Article
Publication status: Published
Journal: SLAS Discovery
Year: 2023
Volume: 28
Issue: 1
Pages: 3-11
Print publication date: 01/01/2023
Online publication date: 19/11/2022
Acceptance date: 15/11/2022
Date deposited: 15/06/2023
ISSN (print): 2472-5552
ISSN (electronic): 2472-5560
Publisher: Society for Laboratory Automation and Screening (SLAS)
URL: https://doi.org/10.1016/j.slasd.2022.11.002
DOI: 10.1016/j.slasd.2022.11.002
PubMed id: 36414185
Altmetrics provided by Altmetric
