ABSTRACT
A CoIII complex (2) of a bispyridine-dioxime ligand (H2LNMe2) containing a tertiary amine group in the proximity of the Co center is synthesized and characterized. One of the oxime protons of the ligand is deprotonated, and the amine group remains protonated in the solid-state structure of the CoII complex (2a). The acid-base properties of 2 showed pKa values of 5.9, 8.4, and 9.6, which are assigned to the dissociation of two consecutive oxime protons and amine protons, respectively. The electrocatalytic proton reduction of 2 was investigated in an aqueous phosphate buffer solution (PBS), revealing a catalytic hydrogen evolution reaction (HER) at an Ecat/2 of -1.01 V vs. the SHE, with an overpotential of 673 mV and a kobs value of 2.6 × 103 s-1 at pH 7. For comparison, the HER of the Co complex (1) lacking the tert-amine group at the secondary sphere was investigated in PBS, which showed a kobs of 1.3 × 103 s-1 and an overpotential of 577 mV. At pH 4, however, 2 revealed a â¼3 times higher kobs value than 1, which suggests that the protonated amine group likely works as a proton relay site. Notably, no significant change in the reaction rate was observed at different pH values for 1, implying that oxime protons may not be involved in the intramolecular proton-coupled electron transfer reaction in the HER. The kobs values for Co complexes at pH 7.0 are significantly higher than those of the [Co(dmgH)2(pyridine)(Cl)] complex, implying that the primary coordination sphere around 1 or 2 enhances the HER and offers better catalyst stability in acidic buffer solutions.
ABSTRACT
A novel tellurium (Te) containing fluorophore, 1 and its nickel (2) and copper (3) containing metal organic complex (MOC) have been synthesized to exploit their structural and optical properties and to deploy these molecules as fluorescent probes for the selective and sensitive detection of picric acid (PA) over other commonly available nitro-explosives. Furthermore, density functional theory (DFT) and single crystal X-ray diffraction (SCXRD) techniques revealed the inclusion of "soft" Tellurium (Te) and "hard" Nitrogen (N), Oxygen (O) atoms in the molecular frameworks. Owing to the presence of electron rich "N" and "O" atoms along with "Te" in the molecular framework, 1 could efficiently and selectively sense PA with more than 80 % fluorescence quenching efficiency in organic medium and having detection limit of 4.60â µM. The selective detection of PA compared to other nitro-explosives follows a multi-mechanism based "turn-off" sensing which includes photo-induced electron transfer (PET), electrostatic (π-π stacking and π-anion/cation) interaction, intermolecular hydrogen bonding and inner filter effect (IFE). The test strip study also establishes the sensitivity of 1 for detection of PA.
ABSTRACT
The binding affinity of the SARS-CoV-2 spike (S)-protein to the human membrane protein ACE2 is critical for virus function. Computational structure-based screening of new S-protein mutations for ACE2 binding lends promise to rationalize virus function directly from protein structure and ideally aid early detection of potentially concerning variants. We used a computational protocol based on cryo-electron microscopy structures of the S-protein to estimate the change in ACE2-affinity due to S-protein mutation (ΔΔGbind) in good trend agreement with experimental ACE2 affinities. We then expanded predictions to all possible S-protein mutations in 21 different S-protein-ACE2 complexes (400,000 ΔΔGbind data points in total), using mutation group comparisons to reduce systematic errors. The results suggest that mutations that have arisen in major variants as a group maintain ACE2 affinity significantly more than random mutations in the total protein, at the interface, and at evolvable sites. Omicron mutations as a group had a modest change in binding affinity compared to mutations in other major variants. The single-mutation effects seem consistent with ACE2 binding being optimized and maintained in omicron, despite increased importance of other selection pressures (antigenic drift), however, epistasis, glycosylation and in vivo conditions will modulate these effects. Computational prediction of SARS-CoV-2 evolution remains far from achieved, but the feasibility of large-scale computation is substantially aided by using many structures and mutation groups rather than single mutation effects, which are very uncertain. Our results demonstrate substantial challenges but indicate ways forward to improve the quality of computer models for assessing SARS-CoV-2 mutation effects.
