Label-free LC-MS based assay to characterize small molecule compound binding to cells.


Journal

SLAS discovery : advancing life sciences R & D
ISSN: 2472-5560
Titre abrégé: SLAS Discov
Pays: United States
ID NLM: 101697563

Informations de publication

Date de publication:
10 2022
Historique:
received: 21 07 2022
revised: 29 08 2022
accepted: 31 08 2022
pubmed: 6 9 2022
medline: 12 10 2022
entrez: 5 9 2022
Statut: ppublish

Résumé

Study of small molecule binding to live cells provides important information on the characterization of ligands pharmacologically. Here we developed and validated a label-free, liquid chromatography-mass spectrometry (LC-MS) based cell binding assay, using centrifugation to separate binders from non-binders. This assay was applied to various target classes, with particular emphasis on those for which protein-based binding assay can be difficult to achieve. In one example, to study a G protein coupled receptor (GPCR), we used one antagonist as probe and multiple other antagonists as competitor ligands. Binding of the probe was confirmed to be specific and saturable, reaching a fast equilibrium. Competition binding analysis by titration of five known ligands suggested a good correlation with their inhibition potency. In another example, this assay was applied to an ion channel target with its agonists, of which the determined binding affinity was consistent with functional assays. This versatile method allows quantitative characterization of ligand binding to cell surface expressed targets in a physiologically relevant environment.

Identifiants

pubmed: 36064100
pii: S2472-5552(22)13692-0
doi: 10.1016/j.slasd.2022.08.005
pii:
doi:

Substances chimiques

Ligands 0
Receptors, G-Protein-Coupled 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

405-412

Informations de copyright

Copyright © 2022. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of Conflicting Interests The authors have declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: All authors are, or were, employed by Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA, and their research and authorship of this article was completed within the scope of their employment. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Menglin Chen (M)

Merck & Co., Inc., Rahway, NJ, USA.

Zhengrong Zhu (Z)

Merck & Co., Inc., Rahway, NJ, USA. Electronic address: Zhengrong.zhu@merck.com.

Tom Wisniewski (T)

Merck & Co., Inc., Rahway, NJ, USA.

Xiaoping Zhang (X)

Merck & Co., Inc., Rahway, NJ, USA.

David G McLaren (DG)

Merck & Co., Inc., Rahway, NJ, USA.

Adam Weinglass (A)

Merck & Co., Inc., Rahway, NJ, USA.

S Adrian Saldanha (SA)

Merck & Co., Inc., Rahway, NJ, USA.

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Classifications MeSH