Complex Formation Equilibria of Unusual Seven-Coordinate Fe(EDTA) Complexes with DNA Constituents and Related Bio-relevant Ligands

Prediction and modeling of pre-analytical sampling errors as a strategy to improve plasma NMR metabolomics data

Motivation

Biobanks are important infrastructures for life science research. Optimal sample handling regarding e.g. collection and processing of biological samples is highly complex, with many variables that could alter sample integrity and even more complex when considering multiple study centers or using legacy samples with limited documentation on sample management. Novel means to understand and take into account such variability would enable high-quality research on archived samples.

Results

This study investigated whether pre-analytical sample variability could be predicted and reduced by modeling alterations in the plasma metabolome, measured by NMR, as a function of pre-centrifugation conditions (1–36 h pre-centrifugation delay time at 4 °C and 22 °C) in 16 individuals. Pre-centrifugation temperature and delay times were predicted using random forest modeling and performance was validated on independent samples. Alterations in the metabolome were modeled at each temperature using a cluster-based approach, revealing reproducible effects of delay time on energy metabolism intermediates at both temperatures, but more pronounced at 22 °C. Moreover, pre-centrifugation delay at 4 °C resulted in large, specific variability at 3 h, predominantly of lipids. Pre-analytical sample handling error correction resulted in significant improvement of data quality, particularly at 22 °C. This approach offers the possibility to predict pre-centrifugation delay temperature and time in biobanked samples before use in costly downstream applications. Moreover, the results suggest potential to decrease the impact of undesired, delay-induced variability. However, these findings need to be validated in multiple, large sample sets and with analytical techniques covering a wider range of the metabolome, such as LC-MS.

Availability and implementation

The sampleDrift R package is available at https://gitlab.com/CarlBrunius/sampleDrift.

Supplementary information

Supplementary data are available at Bioinformatics online.

Photoelectron spectroscopic and computational studies of [EDTA·M(iii)]− complexes (M = H3, Al, Sc, V–Co)

Photoelectron spectroscopic and computational studies of [EDTA·M(iii)]⁻ complexes reveal their redox chemistry and specific metal bindings.

Protonation equilibria of biologically active ligands in mixed aqueous organic solvents

The review is mainly concerned with the protonation equilibria of biologically active ligands like amino acids, peptides, DNA constituents, and amino acid esters in nonaqueous media. Equilibrium concentrations of proton-ligand formation as a function of pH were investigated. Also, thermodynamics associated with protonation equilibria were also discussed.

Bivalent transition metal complexes of cetirizine: spectroscopic, equilibrium studies and biological activity

Metal complexes of cetirizine·2HCl (CTZ=2-[2-[4-[(4-chlorophenyl)phenyl methyl]piperazine-1-yl]-ethoxy]acetic acid, dihydrochloride have been prepared and characterized by elemental analyses, IR, solid reflectance, magnetic moment, molar conductance, and UV-Vis spectra. The analytical data of the complexes show the formation of 1:2 [M:L] ratio, where M represents Ni(II), Co(II) and Cu(II) ions, while L represents the deprotonated CTZ ligand. IR spectra show that CTZ is coordinated to the metal ions in a monodentate manner through carboxylate-O atom. Protonation equilibria of CTZ and its metal complexation by some divalent metal ions were determined in aqueous solution at constant ionic strength (0.1 M NaCl) using an automatic potentiometric technique. Thermodynamic parameters for the protonation equilibria of CTZ were calculated and discussed. The stability order of M(II)-CTZ complexes were found to obey Mn(2+)<Co(2+)<Ni(2+)<Cu(2+), in accordance with the Irving-Williams order. The concentration distribution of the complexes in solution is evaluated as a function of pH. The CTZ ligand and its metal complexes were screened for their biological activity against bacterial species (Bacillus subtillis RCMB 010067, Staphylococcus aureus RCMB 010028, Pseudomonas aeuroginosa RCMB 010043, and Escherichia coli RCMB 010052) and fungi as (Aspergillus flavus RCMB 02568, Pencicillium italicum RCMB 03924, Candida albicans RCMB 05031 and Geotricum candidum RCMB 05097). The activity data show that the metal complexes have antibacterial and antifungal activity more than the parent CTZ ligand against one or more bacterial or fungi species. MIC was evaluated for the isolated complexes.