Preclinical Evaluation of the First Adenosine A1 Receptor Partial Agonist Radioligand for Positron Emission Tomography Imaging.
Min GuoZhan-Guo GaoRyan TylerTyler StoddenYang LiJoseph RamseyWen-Jing ZhaoGene-Jack WangCorinde E WiersJoanna S FowlerKenner C RiceKenneth A JacobsonSung Won KimNora D VolkowPublished in: Journal of medicinal chemistry (2018)
Central adenosine A1 receptor (A1R) is implicated in pain, sleep, substance use disorders, and neurodegenerative diseases, and is an important target for pharmaceutical development. Radiotracers for A1R positron emission tomography (PET) would enable measurement of the dynamic interaction of endogenous adenosine and A1R during the sleep-awake cycle. Although several human A1R PET tracers have been developed, most are xanthine-based antagonists that failed to demonstrate competitive binding against endogenous adenosine. Herein, we explored non-nucleoside (3,5-dicyanopyridine and 5-cyanopyrimidine) templates for developing an agonist A1R PET radiotracer. We synthesized novel analogues, including 2-amino-4-(3-methoxyphenyl)-6-(2-(6-methylpyridin-2-yl)ethyl)pyridine-3,5-dicarbonitrile (MMPD, 22b), a partial A1R agonist of sub-nanomolar affinity. [11C]22b showed suitable blood-brain barrier (BBB) permeability and test-retest reproducibility. Regional brain uptake of [11C]22b was consistent with known brain A1R distribution and was blocked significantly by A1R but not A2AR ligands. [11C]22b is the first BBB-permeable A1R partial agonist PET radiotracer with the promise of detecting endogenous adenosine fluctuations.
Keyphrases
- positron emission tomography
- blood brain barrier
- computed tomography
- pet imaging
- pet ct
- cerebral ischemia
- protein kinase
- endothelial cells
- white matter
- physical activity
- resting state
- high resolution
- sleep quality
- chronic pain
- neuropathic pain
- multiple sclerosis
- mass spectrometry
- functional connectivity
- binding protein
- deep learning
- machine learning
- metabolic syndrome
- artificial intelligence
- molecular dynamics simulations
- cell therapy