Comparison of hydration reactions for "piano-stool" RAPTA-B and [Ru(eta(6) - arene)(en)Cl](+) complexes: Density functional theory computational study

The hydration process for two Ru(II) representative half-sandwich complexes: Ru(arene)(pta)Cl2 (from the RAPTA family) and [Ru(arene)(en)Cl]+ (further labeled as Ru_en) were compared with analogous reaction of cisplatin. In the study, quantum chemical methods were employed. All the complexes were optimized at the B3LYP/6-31G(d) level using Conductor Polarizable Continuum Model (CPCM) solvent continuum model and single-point (SP) energy calculations and determination of electronic properties were performed at the B3LYP/6-311++G(2df,2pd)/CPCM level. It was found that the hydration model works fairly well for the replacement of the first chloride by water where an acceptable agreement for both Gibbs free energies and rate constants was obtained. However, in the second hydration step worse agreement of the experimental and calculated values was achieved. In agreement with experimental values, the rate constants for the first step can be ordered as RAPTA-B > Ru_en > cisplatin. The rate constants correlate well with binding energies (BEs) of the Pt/Ru–Cl bond in the reactant complexes. Substitution reactions on Ru_en and cisplatin complexes proceed only via pseudoassociative (associative interchange) mechanism. On the other hand in the case of RAPTA there is also possible a competitive dissociation mechanism with metastable pentacoordinated intermediate. The first hydration step is slightly endothermic for all three complexes by 3–5 kcal/mol. Estimated BEs confirm that the benzene ligand is relatively weakly bonded assuming the fact that it occupies three coordination positions of the Ru(II) cation

NMR spectroscopic detection of chirality and enantiopurity in referenced systems without formation of diastereomers

Enantiomeric excess of chiral compounds is a key parameter that determines their activity or therapeutic action. The current paradigm for rapid measurement of enantiomeric excess using NMR is based on the formation of diastereomeric complexes between the chiral analyte and a chiral resolving agent, leading to (at least) two species with no symmetry relationship. Here we report an effective method of enantiomeric excess determination using a symmetrical achiral molecule as the resolving agent, which is based on the complexation with analyte (in the fast exchange regime) without the formation of diastereomers. The use of N,N′-disubstituted oxoporphyrinogen as the resolving agent makes this novel method extremely versatile, and appropriate for various chiral analytes including carboxylic acids, esters, alcohols and protected amino acids using the same achiral molecule. The model of sensing mechanism exhibits a fundamental linear response between enantiomeric excess and the observed magnitude of induced chemical shift non-equivalence in the 1H NMR spectra

Biochemical evidence for an alternate pathway in N-linked glycoprotein biosynthesis

Asparagine-linked glycosylation is a complex protein modification conserved among all three domains of life. Herein we report the in vitro analysis of N-linked glycosylation from the methanogenic archaeon Methanococcus voltae. Using a suite of synthetic and semisynthetic substrates, we show that AglK initiates N-linked glycosylation in M. voltae through the formation of α-linked dolichyl monophosphate N-acetylglucosamine, which contrasts with the polyprenyl diphosphate intermediates that feature in both eukaryotes and bacteria. Notably, AglK has high sequence homology to dolichyl phosphate β-glucosyltransferases, including Alg5 in eukaryotes, suggesting a common evolutionary origin. The combined action of the first two enzymes, AglK and AglC, afforded an α-linked dolichyl monophosphate glycan that serves as a competent substrate for the archaeal oligosaccharyl transferase AglB. These studies provide what is to our knowledge the first biochemical evidence revealing that, despite the apparent similarity of the overall pathways, there are actually two general strategies to achieve N-linked glycoproteins across the domains of life.National Institutes of Health (U.S.) (Grant GM039334

In quest of a systematic framework for unifying and defining nanoscience

This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience

Beyond the Hypercube:Evolutionary Accessibility of Fitness Landscapes with Realistic Mutational Networks

Evolutionary pathways describe trajectories of biological evolution in the space of different variants of organisms (genotypes). The probability of existence and the number of evolutionary pathways that lead from a given genotype to a better-adapted genotype are important measures of accessibility of local fitness optima and the reproducibility of evolution. Both quantities have been studied in simple mathematical models where genotypes are represented as binary sequences of two types of basic units, and the network of permitted mutations between the genotypes is a hypercube graph. However, it is unclear how these results translate to the biologically relevant case in which genotypes are represented by sequences of more than two units, for example four nucleotides (DNA) or 20 amino acids (proteins), and the mutational graph is not the hypercube. Here we investigate accessibility of the best-adapted genotype in the general case of K > 2 units. Using computer generated and experimental fitness landscapes we show that accessibility of the global fitness maximum increases with K and can be much higher than for binary sequences. The increase in accessibility comes from the increase in the number of indirect trajectories exploited by evolution for higher K. As one of the consequences, the fraction of genotypes that are accessible increases by three orders of magnitude when the number of units K increases from 2 to 16 for landscapes of size N ∼ 106 genotypes. This suggests that evolution can follow many different trajectories on such landscapes and the reconstruction of evolutionary pathways from experimental data might be an extremely difficult task