Predicting the Thermodynamic Stability of Zirconium Radiotracers.
Jason P HollandPublished in: Inorganic chemistry (2020)
The thermodynamic stability of a metal-ligand complex, as measured by the formation constant (log β), is one of the most important parameters that determines metal ion selectivity and potential applications in, for example, radiopharmaceutical science. The stable coordination chemistry of radioactive 89Zr4+ in an aqueous environment is of paramount importance when developing positron-emitting radiotracers based on proteins (usually antibodies) for use with positron emission tomography. Desferrioxamine B (DFO) remains the chelate of choice for clinical applications of 89Zr-labeled proteins, but the coordination of DFO to Zr4+ ions is suboptimal. Many alternative ligands have been reported, but the challenges in measuring very high log β values with metal ions such as Zr4+ that tend to hydrolyze mean that accurate thermodynamic data are scarce. In this work, density functional theory (DFT) calculations were used to predict the reaction energetics for metal ion complexation. Computed values of pseudoformation constants (log β') are correlated with experimental data and showed an excellent linear relationship (R2 = 0.97). The model was then used to estimate the absolute and relative formation constants of 23 different Zr4+ complexes using a total of 17 different ligands, including many of the alternative bifunctional chelates that have been reported recently for use in 89Zr4+ radiochemistry. In addition, detailed computational studies were performed on the geometric isomerism and hydration state of Zr-desferrioxamine. Collectively, the results offer new insights into Zr4+ coordination chemistry that will help guide the synthesis of future ligands. The computational model developed here is straightforward and reproducible and can be readily applied in the design of other metal coordination compounds.
Keyphrases
- pet imaging
- positron emission tomography
- density functional theory
- computed tomography
- molecular dynamics
- quantum dots
- electronic health record
- public health
- magnetic resonance imaging
- high resolution
- big data
- mass spectrometry
- molecular docking
- risk assessment
- magnetic resonance
- deep learning
- artificial intelligence
- pet ct
- fluorescent probe
- diffusion weighted imaging