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Accelerated Screening of Protein-Ligand Interactions via Parallel T2-Weighted 19F-MRI
Dilara Faderl1, Ajmal Chenakkara1, Mazin Jouda1
1Institute of Microstructure Technology, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen, Germany.
Analytical Chemistry
|June 3, 2024
Summary
Magnetic resonance imaging (MRI) offers a parallel approach to drug discovery screening. This study demonstrates 19F-MRI for detecting protein-ligand binding and determining ligand affinity, enhancing throughput in biochemical assays.
Area of Science:
- Biophysics
- Chemical Biology
- Drug Discovery
Background:
- Ligand screening is crucial for drug discovery, but current methods like Nuclear Magnetic Resonance (NMR) have limited throughput.
- Magnetic Resonance Imaging (MRI) offers inherent parallelism and can encode parameters in images, suggesting potential for higher throughput screening.
Purpose of the Study:
- To explore the application of 19F-MRI for parallel characterization of protein-ligand interactions.
- To demonstrate the detection of ligand binding and determination of ligand affinity using 19F-MRI.
Main Methods:
- Utilized a custom-built 9-fold sample holder and a 19F-MRI coil for parallel measurements.
- Employed T2-weighted 19F-MRI to detect binding of 4-(trifluoromethyl)benzamidine (TFBA) to trypsin.
- Determined the affinity of non-fluorinated ligands via competition assays by monitoring TFBA displacement.
Main Results:
- Successfully detected ligand binding using T2-weighted 19F-MRI.
- Demonstrated parallel determination of non-fluorinated ligand affinity through dose-dependent displacement of TFBA.
- Derived the affinity of benzamidine (BA) by comparing parallel 19F-T2-weighted MR images.
Conclusions:
- 19F-MRI enables parallel characterization of protein-ligand interactions, significantly increasing throughput for biochemical assays.
- This approach holds promise for drug discovery, with potential for enhanced sensitivity when combined with hyperpolarization techniques.

