Phosphonate Chelators for Medicinal Metal Ions

A family of phosphonate-bearing chelators was synthesized to study their potential in metal-based (radio)- pharmaceuticals. Three ligands (H6phospa, H6dipedpa, H6eppy; structures illustrated in manuscript) were fully characterized, including X-ray crystallographic structures of H6phospa and H6dipedpa. NMR spectroscopy techniques were used to confirm the complexation of each ligand with selected trivalent metal ions. These methods were particularly useful in discerning structural information for Sc3+ and La3+ complexes. Solution studies were conducted to evaluate the complex stability of 15 metal complexes. As a general trend, H6phospa was noted to form the most stable complexes, and H6eppy associated with the least stable complexes. Moreover, In3+ complexes were determined to be the most stable, and complexes with La3+ were the least stable, across all metals. Density functional theory (DFT) was employed to calculate structures of H6phospa and H6dipedpa complexes with La3+ and Sc3+. A comparison of experimental 1 H NMR spectra with calculated 1 H NMR spectra using DFT-optimized structures was used as a method of structure validation. It was noted that theoretical NMR spectra were very sensitive to a number of variables, such as ligand configuration, protonation state, and the number/orientation of explicit water molecules. In general, the inclusion of an explicit second shell of water molecules qualitatively improved the agreement between theoretical and experimental NMR spectra versus a polarizable continuum solvent model alone. Formation constants were also calculated from DFT results using potential-energy optimized structures. Strong dependence of molecular free energies on explicit water molecule number, water molecule configuration, and protonation state was observed, highlighting the need for dynamic data in accurate first-principles calculations of metal−ligand stability constants

Lithium halide structural chemistry : computational analysis with machine learning, quantum chemistry, and molecular dynamics

The lithium halide salts may at first appear to be simple chemical systems. However, previous research indicates lithium halides have complex and poorly understood crystallization pathways from aqueous solutions. While lithium halides exist in the rocksalt crystal structure under ambient conditions, common lithium halide classical force fields more often predict wurtzite as the stable structure. This failure severely limits their application in molecular simulations of crystallization. Research in this thesis focuses on presenting new results and computational methodology to better understand the structural chemistry of both lithium halides and alkali halides in general. Density functional theory together with classical force fields are employed to examine the relative stability of candidate crystal structures for lithium halides and produce accurate theoretical reference data. Dispersion interactions are shown to play a key role in the stability of rocksalt over closely competing crystal structures. Classical models can be corrected in their structural predictions by scaling up the strength of dispersion, indicating a pathway towards better lithium halide force fields. Convolutional neural networks are used for the structural classification of simulated alkali halides. The neural networks are trained on a large data set generated from molecular dynamics simulations of alkali halides across a range of temperatures. Time convolution filters out short-lived structural fluctuations. The structure classifiers are shown to be accurate in bulk phase simulations, then demonstrated on crystallization of model alkali halide systems from the melt. The neural network classifiers are implemented in a melting point calculation algorithm for model binary salts. Finite size effects are characterized, then melting points of alkali halides using common rigid-ion interaction potentials are calculated and discussed. The methods developed throughout the research are employed for the optimization of pairwise lithium halide force fields, fitted to reference data using a reinforcement learning approach, Bayesian optimization. Limitations on the Coulomb Lennard-Jones potential form are uncovered, which do not appear to hold for the more flexible Coulomb Buckingham potential form. By introducing advanced computational methodology, this research reveals the inherent structural complexity of lithium halides and emphasizes the importance of considering structural landscapes during classical forcefields construction for molecular simulation.Science, Faculty ofChemistry, Department ofGraduat

molecular dynamics for weakly-interacting systems

Within the framework of linear-scaling Kohn-Sham density functional theory, a robust method for maintaining compact localized orbitals close to the ground state is coupled with nuclear dynamics. This allows to obviate the commonly employed optimization of the one-electron density matrix and thus create an efficient orbital-only molecular dynamics method for weakly-interacting systems. An application to liquid water demonstrates that the low computational overhead of the method makes it well-suited for routine simulations whereas its linear-scaling complexity allows to extend first-principle dynamical studies of molecular systems to previously inaccessible length scales.Comment: 5 pages, 4 figure

Contribution of the Covalent Component of the Hydrogen-Bond Network to the Properties of Liquid Water

Many remarkable properties of liquid water originate from the ability of its molecules to form hydrogen bonds, each of which emerges as a combination of electrostatic, polarization, dispersion, and donor–acceptor or covalent interactions. In this work, ab initio molecular dynamics was tailored to isolate and switch off the covalent component of interactions between water molecules in simulations. Comparison of simulations with and without covalency shows that a small amount of intermolecular electron density transfer has a profound effect on the structure and dynamics of the hydrogen-bond network and thus on observable properties of room-temperature liquid water

H₄HBEDpa: Octadentate Chelate after A. E. Martell

H4HBEDpa, a new octadentate chelator inspired by the 1960s ligand HBED of Arthur E. Martell, has been investigated for a selection of trivalent metal ions useful in diagnostic and therapeutic applications (Sc3+, Fe3+, Ga3+, In3+, and Lu3+). Complex formation equilibria were thoroughly investigated using combined potentiometric and UV–vis spectrophotometric titrations which revealed effective chelation and high metal-sequestering capacity, in particular for Fe3+, log KFeL = 36.62, [Fe­(HBEDpa)]−. X-ray diffraction study of single crystals revealed that the ligand is preorganized and forms hexa-coordinated complexes with Fe3+ and Ga3+ at acidic pH. Density functional theory (DFT) calculations were applied to probe the geometries and energies of all the possible conformers of [M­(HBEDpa)]− (M = Sc3+, Fe3+, Ga3+, In3+, and Lu3+). DFT calculations confirmed the experimental findings, indicating that [Fe­(HBEDpa)]− is bound tightly in an asymmetric pattern as compared to the symmetrically bound and more open [Ga­(HBEDpa)]−, prone to hydrolysis at higher pH. DFT calculations also showed that a large metal ion such as Lu3+ fully coordinates with HBEDpa4–, forming a binary octadentate complex in its lowest-energy form. Smaller metal ions form six or seven coordinate complexes with HBEDpa4–