Insights into the Reaction Mechanism of Aromatic Ring Cleavage by Homogentisate Dioxygenase: A Quantum Mechanical/Molecular Mechanical Study

To elucidate the reaction mechanism of the ring cleavage of homogentisate by homogentisate dioxygenase, quantum mechanical/molecular mechanical (QM/MM) calculations were carried out by using two systems in different protonation states of the substrate C₂ hydroxyl group. When the substrate C₂ hydroxyl group is ionized (the ionized pathway), the superoxo attack on the substrate is the rate-limiting step in the catalytic cycle, with a barrier of 15.9 kcal/mol. Glu396 was found to play an important role in stabilizing the bridge species and its O–O cleavage product by donating a proton via a hydrogen-bonded water molecule. When the substrate C₂ hydroxyl group is not ionized (the nonionized pathway), the O–O bond cleavage of the bridge species is the rate-limiting step, with a barrier of 15.3 kcal/mol. The QM/MM-optimized geometries for the dioxygen and alkylperoxo complexes using the nonionized model (for the C₂ hydroxyl group) are in agreement with the experimental crystal structures, suggesting that the C₂ hydroxyl group is more likely to be nonionized

Self-Reported Negative Emotion Ratings.

<p>Self-reported negative emotion ratings of choice in each loss condition. Losing T in TV was rated as the least negative, followed by T in TR and R in TR, with V in TV rated as the most negative (<i>ps</i><.01), even though the choice difficulty was controlled.</p

Self-Reported Negative Emotion Ratings and Response Times.

<p>a) Self-reported negative emotion ratings of choice in each loss decision condition. b) Self-reported difficulty ratings of choice in each loss decision condition. c) Mean response time (in milliseconds) in each loss decision condition.</p

Self-Reported Importance Ratings and Response Times.

<p>a) Self-reported importance ratings for alternatives in each loss decision condition. b) Self-reported choice difficulty ratings in each loss decision condition. c) Mean response time (in milliseconds) in each loss decision condition.</p

The average latencies of fixation on a new object and average number of trials in which onsets were fixated for all conditions in Experiment 2.

<p>The average latencies of fixation on a new object and average number of trials in which onsets were fixated for all conditions in Experiment 2.</p

Breast cancer-associated mutations in human ADAM12-L.

<p>(A) A diagram of human ADAM12-L. Six non-synonymous mutations identified in human breast cancers are indicated. S, signal peptide; P, prodomain; M, metalloproteinase domain; D, disintegrin domain; C, cysteine-rich domain; E, EGF-like domain; T, transmembrane region; Cyt, cytoplasmic tail. (B) Model of the extracellular domain of human ADAM12-L generated by the I-TASSER protein structure prediction tool (C-score <i>−</i>0.26, estimated TM accuracy of the model 0.68±0.12 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092536#pone.0092536-Roy2" target="_blank">[20]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092536#pone.0092536-Zhang1" target="_blank">[21]</a>). The metalloproteinase, disintegrin, cysteine-rich, and EGF-like domains are shown in purple, blue, yellow, and green, respectively. Positions of the five amino acids mutated in breast cancers (red spheres) and the side chain of the catalytic residue E351 (cyan sticks) are indicated. (C) Sequence alignment of the cysteine-rich and EGF-like domains of ADAM12 from different species. NCBI RefSeq numbers are: <i>Homo_sapiens</i>, NP_003465; <i>Mus_musculus</i>, NP_031426; <i>Rattus_norvegicus</i>, XP_001054670; <i>Bos_taurus</i>, NP_001001156, <i>Equus_caballus</i>, XP_001490097; <i>Gallus_gallus</i>, NP_001136322, and <i>Xenopus_tropicalis</i>, NP_001035103. (D) Sequence alignment of the cysteine-rich and EGF-like domains of human ADAM12 and the most closely related human ADAMs. NCBI RefSeq numbers are: ADAM19, XP_005266060, ADAM33, NP_079496.1, and ADAM15, NP_997080. In C and D, asterisks indicate three novel mutations in human ADAM12 found in breast tumors <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092536#pone.0092536-Shah1" target="_blank">[14]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092536#pone.0092536-Jiao1" target="_blank">[15]</a>. Clustal X color scheme was applied.</p

Integrated Computation and Experimental Investigation on the Adsorption Mechanisms of Anti-Wear and Anti-Corrosion Additives on Copper

We integrated first-principles calculations and surface characterization techniques to reveal a new molecular adsorption mechanism of antiwear (dialkyl dithiophosphate ester, EAK) and anticorrosion (2,5-bis­(ethyldisulfanyl)-1,3,4-thiadiazole, DTA) additives on the Cu surface during the rolling process. For direct comparison of modeling and experiments, the Cu(110) surface was used in the model based on the strong (220) preferred orientation observed in the microstructures of the rolled copper foil. Density functional theory (DFT) calculations were performed to obtain the adsorption energy, the optimized adsorption structures, and the charge transfer due to adsorption for EAK and DTA on the Cu(110) surface. It was found that the anticorrosion additive, DTA, decomposed and chemically adsorbed on the Cu(110) surface strongly via multiple Cu–N and Cu–S bonds, while the antiwear additive, EAK, adsorbed weakly due to one Cu–O bond. The predicted chemical bonds formation with the Cu surface reasonably agreed with X-ray photoelectron spectroscopy (XPS) analysis. A new anticorrosion mechanism, due to DTA decomposition and stronger chemisorption than that of EAK, was therefore proposed based on the simulation

The sequence of events of two trials in Experiment 1.

<p>The target letter “H” or “S” can be either an onset target or a non-onset target.</p

Fixation results in the non-onset target condition of Experiment 1.

<p>Panel A illustrates the probability of fixating new objects under the non-onset target condition in Experiment 1; Panel B illustrates the probability of first look to onset for the three mask types under the non-onset target condition in Experiment 1.</p

The mean accuracy of the three mask conditions in Experiment 2.

<p>The mean accuracy of the three mask conditions in Experiment 2.</p