Reaction rates for O + HD → OH + D and O + HD → OD + H

We have calculated reaction rates for the reactions O + HD → OH + D and O + DH → OD + H using improved canonical variational transition state theory and least-action ground-state transmission coefficients with an ab initio potential energy surface. The kinetic isotope effects are in good agreement with experiment. The optimized tunneling paths and properties of the variational transition states and the rate enhancement for vibrationally excited reactants are also presented and compared with those for the isotopically unsubstituted reaction O + H₂ → OH + H. The thermal reactions at low and room temperature are predicted to occur by tunneling at extended configurations, i.e., to initiate early on the reaction path and to avoid the saddle point regions. Tunneling also dominates the low and room temperature reactions for excited vibrational states, but in these cases the results are not as sensitive to the nature of the tunneling path. Overbarrier mechanisms dominate for both thermal and excited-vibrational state reactions for T > 600 K. For the excited-state reaction (with initial vibrational quantum number n > 0) a transition state switch occurs for T > 1000 K for the O + HD(n = 1) → OD + H case and for T > 1500 K for the O + DH(n = 1) → OD + H reaction, and this may be a general phenomenon for excited-state reactions at higher temperature. In the present case the switch occurs from an early variational transition state where the vibrationally adiabatic approximation is expected to be valid to a tighter variational transition state where nonadiabatic effects are probably important and should be included.     

Ligand requirements for glmS ribozyme self-cleavage

Natural RNA catalysts (ribozymes) perform essential reactions in biological RNA processing and protein synthesis, whereby catalysis is intrinsic to RNA structure alone or in combination with metal ion cofactors. The recently discovered glmS ribozyme is unique in that it functions as a glucosamine-6-phosphate (GlcN6P)-dependent catalyst believed to enable "riboswitch" regulation of amino-sugar biosynthesis in certain prokaryotes. However, it is unclear whether GlcN6P functions as an effector or coenzyme to promote ribozyme self-cleavage. Herein, we demonstrate that ligand is absolutely requisite for glmS ribozyme self-cleavage activity. Furthermore, catalysis both requires and is dependent upon the acid dissociation constant (pKa) of the amine functionality of GlcN6P and related compounds. The data demonstrate that ligand is integral to catalysis, consistent with a coenzyme role for GlcN6P and illustrating an expanded capacity for biological RNA catalysis.     

On the first excited state of137Ba

The first excited state of¹³⁷Ba has been excited by the inelastic scattering of accelerator-produced neutrons. The energy of this state at 283.5 keV is not in agreement with the generally accepted value of 279.2 keV, but is in accord with other recent measurements. No evidence for a doublet of states near this energy is found.     

Completely automated, highly error-tolerant macromolecular structure determination from multidimensional nuclear overhauser enhancement spectra and chemical shift assignments

The major rate-limiting step in high-throughput NMR protein structure determination involves the calculation of a reliable initial fold, the elimination of incorrect nuclear Overhauser enhancement (NOE) assignments, and the resolution of NOE assignment ambiguities. We present a robust approach to automatically calculate structures with a backbone coordinate accuracy of 1.0-1.5 A from datasets in which as much as 80% of the long-range NOE information (i.e., between residues separated by more than five positions in the sequence) is incorrect. The current algorithm differs from previously published methods in that it has been expressly designed to ensure that the results from successive cycles are not biased by the global fold of structures generated in preceding cycles. Consequently, the method is highly error tolerant and is not easily funnelled down an incorrect path in either three-dimensional structure or NOE assignment space. The algorithm incorporates three main features: a linear energy function representation of the NOE restraints to allow maximization of the number of simultaneously satisfied restraints during the course of simulated annealing; a method for handling the presence of multiple possible assignments for each NOE cross-peak which avoids local minima by treating each possible assignment as if it were an independent restraint; and a probabilistic method to permit both inactivation and reactivation of all NOE restraints on the fly during the course of simulated annealing. NOE restraints are never removed permanently, thereby significantly reducing the likelihood of becoming trapped in a false minimum of NOE assignment space. The effectiveness of the algorithm is demonstrated using completely automatically peak-picked experimental NOE data from two proteins: interleukin-4 (136 residues) and cyanovirin-N (101 residues). The limits of the method are explored using simulated data on the 56-residue B1 domain of Streptococcal protein G.     

One-Step Generalized Estimating Equations With Large Cluster Sizes

Medical studies increasingly involve a large sample of independent clusters, where the cluster sizes are also large. Our motivating example from the 2010 Nationwide Inpatient Sample (NIS) has 8,001,068 patients and 1049 clusters, with average cluster size of 7627. Consistent parameter estimates can be obtained naively assuming independence, which are inefficient when the intra-cluster correlation (ICC) is high. Efficient generalized estimating equations (GEE) incorporate the ICC and sum all pairs of observations within a cluster when estimating the ICC. For the 2010 NIS, there are 92.6 billion pairs of observations, making summation of pairs computationally prohibitive. We propose a one-step GEE estimator that (1) matches the asymptotic efficiency of the fully iterated GEE; (2) uses a simpler formula to estimate the ICC that avoids summing over all pairs; and (3) completely avoids matrix multiplications and inversions. These three features make the proposed estimator much less computationally intensive, especially with large cluster sizes. A unique contribution of this article is that it expresses the GEE estimating equations incorporating the ICC as a simple sum of vectors and scalars.     

Constant pH Molecular Dynamics Simulations of Nucleic Acids in Explicit Solvent

The nucleosides of adenine and cytosine have pKa values of 3.50 and 4.08, respectively, and are assumed to be unprotonated under physiological conditions. However, evidence from recent NMR and X-Ray crystallography studies has revealed the prevalence of protonated adenine and cytosine in RNA macromolecules. Such nucleotides with elevated pKa values may play a role in stabilizing RNA structure and participate in the mechanism of ribozyme catalysis. With the work presented here, we establish the framework and demonstrate the first constant pH MD simulations (CPHMD) for nucleic acids in explicit solvent in which the protonation state is coupled to the dynamical evolution of the RNA system via λ-dynamics. We adopt the new functional form λ(Nexp) for λ that was recently developed for Multi-Site λ-Dynamics (MSλD) and demonstrate good sampling characteristics in which rapid and frequent transitions between the protonated and unprotonated states at pH = pKa are achieved. Our calculated pKa values of simple nucleotides are in a good agreement with experimentally measured values, with a mean absolute error of 0.24 pKa units. This work demonstrates that CPHMD can be used as a powerful tool to investigate pH-dependent biological properties of RNA macromolecules.     

Characterization of the patina formed on a low tin bronze exposed to aqueous hydrogen sulfide

The dark gray corrosion layer (patina) formed on the surface of a polished low tin bronze alloy following exposure to a deoxygenated and saturated aqueous solutions of H₂S has been characterized by X‐ray photoelectron spectroscopy, scanning electron microscopy‐energy dispersive spectroscopy and X‐ray diffraction. The system represents a model for bronze corrosion in reducing conditions where sulfate‐reducing bacteria in soils or deoxygenated seawater may generate H₂S during respiration. The initial surface was dominated by metallic copper together with Sn, Pb and Zn oxides and hydroxides. Surface enrichment of Pb and Zn was noted because of a smearing effect during polishing. At least some of the lead was crystalline. In contrast, the corrosion layer formed by H₂S(aq) exposure was dominated by polycrystalline Cu₂S (low and high chalcocite) and smaller concentrations of CuSO₄ · nH₂O. This surface was enriched with Zn as Zn(OH)₂. Lead was present as redeposited PbS (galena) crystallites in at least two different morphologies. Unlike bronzes exposed to oxidizing conditions, which develop protective SnO₂ layers, the H₂S(aq)‐exposed surface was considerably depleted in Sn. Copyright © 2014 John Wiley & Sons, Ltd.