RESUMEN
The role of urea as a kinetic promoter for the growth of CO2 hydrates is revealed for the first time using molecular dynamics simulations. Analysis of simulation trajectories shows that urea plays two important roles in the growth process: increasing mass transport of CO2 and catalyzing cage formation at the solid-liquid interface.
Asunto(s)
Dióxido de Carbono/química , Simulación de Dinámica Molecular , Urea/química , Tamaño de la Partícula , Agua/químicaRESUMEN
The intrinsic nature of glycosylation, namely nontemplate encoded, stepwise elongation and termination with a diverse range of isomeric glyco-epitopes (glycotopes), translates into ambiguity in most cases of mass spectrometry (MS)-based glycomic mapping. It is arguable that whether one needs to delineate every single glycomic entity, which may be counterproductive. Instead, one should focus on identifying as many structural features as possible that would collectively define the glycomic characteristics of a cell or tissue, and how these may change in response to self-programmed development, immuno-activation, and malignant transformation. We have been pursuing this line of analytical strategy that homes in on identifying the terminal sulfo-, sialyl, and/or fucosylated glycotopes by comprehensive nanoLC-MS2-product dependent MS3 analysis of permethylated glycans, in conjunction with development of a data mining computational tool, GlyPick, to enable an automated, high throughput, semi-quantitative glycotope-centric glycomic mapping amenable to even nonexperts. We demonstrate in this work that diagnostic MS2 ions can be relied on to inform the presence of specific glycotopes, whereas their possible isomeric identities can be resolved at MS3 level. Both MS2 and associated MS3 data can be acquired exhaustively and processed automatically by GlyPick. The high acquisition speed, resolution, and mass accuracy afforded by top-notch Orbitrap Fusion MS system now allow a sensible spectral count and/or summed ion intensity-based glycome-wide glycotope quantification. We report here the technical aspects, reproducibility and optimization of such an analytical approach that uses the same acidic reverse phase C18 nanoLC conditions fully compatible with proteomic analysis to allow rapid hassle-free switching. We further show how this workflow is particularly effective when applied to larger, multiply sialylated and fucosylated N-glycans derived from mouse brain. The complexity of their terminal glycotopes including variants of fucosylated and disialylated type 1 and 2 chains would otherwise not be adequately delineated by any conventional LC-MS/MS analysis.