RESUMEN
Kinetic proofreading is used throughout natural systems to enhance the specificity of molecular recognition. At its most basic level, kinetic proofreading uses a supply of chemical fuel to drive a recognition interaction out of equilibrium, allowing a single free-energy difference between correct and incorrect targets to be exploited two or more times. Despite its importance in biology, there has been little effort to incorporate kinetic proofreading into synthetic systems in which molecular recognition is important, such as nucleic acid nanotechnology. In this article, we introduce a DNA strand displacement-based kinetic proofreading motif, showing that the consumption of a DNA-based fuel can be used to enhance molecular recognition during a templated dimerization reaction. We then show that kinetic proofreading can enhance the specificity with which a probe discriminates single nucleotide mutations, both in terms of the initial rate with which the probe reacts and the long-time behavior.
Asunto(s)
ADN , Cinética , ADN/química , DimerizaciónRESUMEN
Differences in catalyst deactivation kinetics in solid acid catalysis are studied with catalyst models that allow for lateral interaction between protons. Deactivation of a solid acid catalyst with laterally interacting protons induces inhomogeneity of proton reactivity that develops with time. As a consequence, product selectivity changes and deactivation will accelerate. This is demonstrated by simulations of the deactivation kinetics of the alkylation reaction of propylene with isobutane. The effect of lateral interactions between protons arises because initial catalyst deactivation is not caused by pore blocking or coke deposition but by a molecular mechanism where protons are consumed due to the formation of stable nonreactive carbenium ions. High selectivity to alkylate requires a catalyst with protons of high reactivity. When protons become consumed by formation of stable deactivating carbenium ions, initially reactive protons are converted into protons of lower reactivity. The latter only catalyze deactivating oligomerization reactions. Simulations that compare the deactivation kinetics of a catalyst model with laterally interacting protons and a catalyst model that contains protons of similar but different reactivity, but that do not laterally interact, are compared. These simulations demonstrate that the lateral interaction catalyst model is initially more selective but also has a lower stability. Catalyst deactivation of the alkylation reaction occurs through two reaction channels. One reaction channel is due to oligomerization of reactant propylene. The other deactivation reaction channel is initiated by deprotonation of intermediate carbenium ions that increase alkene concentration. By consecutive reactions, this also leads to deactivation. The hydride transfer reaction competes with oligomerization reactions. It is favored by strongly acid sites that also suppress the deprotonation reaction. Within the laterally interacting proton catalyst model, when reactive protons become deactivated, weakly reactive protons are generated that only catalyze the deactivating alkene oligomerization and consecutive reactions. This rapid formation of the weakly reactive protons is the cause of decreasing selectivity with reaction time and increased rate of deactivation. Solutions of the mean field kinetic equations as well as stochastic simulations are presented. Comparative simulations with a reduced number of neighbors of the protons illustrate decreased deactivation rates when the proton density decreases. Island formation of adsorbed reaction intermediates on the catalyst surface is observed in stochastic kinetics simulations. When alkylation selectivity is high, this island formation increases the rate of catalyst deactivation in comparison to the rate of deactivation according to the mean field studies. A nonlinear dynamics model of proton dynamics is provided, which shows that the differences between stochastic and mean field simulations are due to frustrated proton state percolation.
RESUMEN
New insights and successful use of computational catalysis are highlighted. This is within the context of remaining issues that prevent theoretical catalysis to be fully predictive of catalyst performance. A major challenge is to include in modelling studies the transient initiation as well as deactivation processes of the catalyst. We will illustrate this using as an example for solid acid catalysis, the alkylation process, and for transition metal catalysis, the Fischer-Tropsch reaction. For the alkylation reaction of isobutane and alkene, an important reaction for high octane gasoline, we will present a deactivation model. For the Fischer-Tropsch reaction, which converts synthesis gas into gasoline grade molecules, we discuss structural reorganization of the catalyst induced by reaction.
RESUMEN
Cystic fibrosis (CF) is an autosomal recessive disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. CFTR is a member of the adenosine triphosphate (ATP)-binding cassette superfamily of proteins and it functions as a chloride channel. CFTR largely controls the working of epithelial cells of the airways, the gastrointestinal tract, exocrine glands, and genitourinary system. Cystic fibrosis is responsible for severe chronic pulmonary disorders in children. Other maladies in the spectrum of this life-limiting disorder include nasal polyposis, pansinusitis, rectal prolapse, pancreatitis, cholelithiasis, insulin-dependent hyperglycemia, and cirrhosis. This review summarizes the recent state of art in the field of cystic fibrosis diagnostic methods with the help of CF literature published so far and proposes new research domains in the field of cystic fibrosis diagnosis.