Tetraloop‐like Geometries Could Form the Basis of the Catalytic Activity of the Most Ancient Ribooligonucleotides

The origin of the catalytic activity of ancient oligonucleotides is a largely unexplored field of contemporary science. In the current work we use molecular dynamics simulations to investigate the plausibility of tetraloop‐like overhang geometries to initiate transphosphorylation reactions that lead to ligation and terminal cleavage in simple, Watson–Crick (WC) complementary oligoC/oligoG sequences observed experimentally. We show a series of examples of known tetraloop architectures, which can be adopted by the unpaired overhangs of short oligonucleotide sequences for a sufficiently long time to enable chemical reactions that lead to simple ribozyme‐like catalytic activity. Thus, our computations demonstrate that the role of non‐WC interactions at the emergence of the most ancient catalytic oligonucleotides could be more significant than ever believed.     

Self-Assembly of Nanoparticles into Two-Dimensional Arrays for Catalytic Applications

Self-assembly of nanoparticles (NPs) is at the heart of nanotechnology, and has shown many potential applications in fabricating nanodevices with highly controlled functionality. Two-dimensional (2D) arrays of NPs can provide a thin and uniform NP array with each NP being exposed on the surface to maximize NP catalysis. This minireview summarizes the recent progress on the fabrication and application of 2D NP arrays. It conveys the important message to readers that creation of libraries of NP arrays with varying catalytic strengths is an exciting direction in catalysis. This approach can be used to solve complicated catalytic problems in which multiple chemical reactions need to be catalyzed in a single reaction vessel.     

Catalysis‐Driven Self‐Thermophoresis of Janus Plasmonic Nanomotors

It is highly demanding to design active nanomotors that can move in response to specific signals with controllable rate and direction. A catalysis‐driven nanomotor was constructed by designing catalytically and plasmonically active Janus gold nanoparticles (Au NPs), which generate an asymmetric temperature gradient of local solvent surrounding NPs in catalytic reactions. The self‐thermophoresis behavior of the Janus nanomotor is monitored from its inherent plasmonic response. The diffusion coefficient of the self‐thermophoresis motion is linearly dependent on chemical reaction rate, as described by a stochastic model.     

Stochastic hybrid modeling of intracellular calcium dynamics

Deterministic models of biochemical processes at the subcellular level might become inadequate when a cascade of chemical reactions is induced by a few molecules. Inherent randomness of such phenomena calls for the use of stochastic simulations. However, being computationally intensive, such simulations become infeasible for large and complex reaction networks. To improve their computational efficiency in handling these networks, we present a hybrid approach, in which slow reactions and fluxes are handled through exact stochastic simulation and their fast counterparts are treated partially deterministically through chemical Langevin equation. The classification of reactions as fast or slow is accompanied by the assumption that in the time-scale of fast reactions, slow reactions do not occur and hence do not affect the probability of the state. Our new approach also handles reactions with complex rate expressions such as Michaelis-Menten kinetics. Fluxes which cannot be modeled explicitly through reactions, such as flux of Ca(2+) from endoplasmic reticulum to the cytosol through inositol 1,4,5-trisphosphate receptor channels, are handled deterministically. The proposed hybrid algorithm is used to model the regulation of the dynamics of cytosolic calcium ions in mouse macrophage RAW 264.7 cells. At relatively large number of molecules, the response characteristics obtained with the stochastic and deterministic simulations coincide, which validates our approach in the limit of large numbers. At low doses, the response characteristics of some key chemical species, such as levels of cytosolic calcium, predicted with stochastic simulations, differ quantitatively from their deterministic counterparts. These observations are ubiquitous throughout dose response, sensitivity, and gene-knockdown response analyses. While the relative differences between the peak-heights of the cytosolic [Ca(2+)] time-courses obtained from stochastic (mean of 16 realizations) and deterministic simulations are merely 1%-4% for most perturbations, it is specially sensitive to levels of G(βγ) (relative difference as large as 90% at very low G(βγ)).     

Catalytic Enantioselective Radical Transformations Enabled by Visible Light

Visible light has been recognized as an economical and environmentally benign source of energy that enables chemoselective molecular activation of chemical reactions and hence reveal a new horizon for the design and discovery of novel chemical transformations. On the other hand, asymmetric catalysis represents an economic method to satisfy the increasing need for enantioenriched compounds in the chemical and pharmaceutical industries. Therefore, combining visible light photocatalysis with asymmetric catalysis creates a wider range of opportunities for the development of mechanistically unique reaction schemes. However, there arise two main problems like undesirable photochemical background reactions and difficulties in controlling the stereochemistry with highly reactive photochemical intermediates which can pose a serious challenge to the development of asymmetric visible light photocatalysis. In recent years, several methods have been developed to overcome these challenges. This review summarizes the recent advances in visible light‐induced enantioselective reactions. We divide our discussion into four categories: Asymmetric photoredox organocatalysis, asymmetric transition metal photoredox catalysis, asymmetric photoredox Lewis acid catalysis and asymmetric photoinduced energy transfer catalysis. Special emphasis has been given to different catalytic activation modes that enable the construction of challenging carbon‐carbon and carbon‐heteroatom bond in an enantioselective fashion. A brief analysis of substrate scope and limitation as well as reaction mechanism of these reactions has been included.     

Effect of hydrodynamic interactions on the evolution of chemically reactive ternary mixtures

We investigate the structural evolution of an A/B/C ternary mixture in which the A and B components can undergo a reversible chemical reaction to form C. We developed a lattice Boltzmann model for this ternary mixture that allows us to capture both the reaction kinetics and the hydrodynamic interactions within the system. We use this model to study a specific reactive mixture in which C acts as a surfactant, i.e., the formation of C at the A/B interface decreases the interfacial tension between the A and B domains. We found that the dynamics of the system is different for fluids in the diffusive and viscous regimes. In the diffusive regime, the formation of a layer of C at the interface leads to a freezing of the structural evolution in the fluid; the values of the reaction rate constants determine the characteristic domain size in the system. In the viscous regime, where hydrodynamic interactions are important, interfacial reactions cause a slowing down of the domain growth, but do not arrest the evolution of the mixture. The results provide guidelines for controlling the morphology of this complex ternary fluid.     

Efficient stochastic simulations of complex reaction networks on surfaces

Surfaces serve as highly efficient catalysts for a vast variety of chemical reactions. Typically, such surface reactions involve billions of molecules which diffuse and react over macroscopic areas. Therefore, stochastic fluctuations are negligible and the reaction rates can be evaluated using rate equations, which are based on the mean-field approximation. However, in case that the surface is partitioned into a large number of disconnected microscopic domains, the number of reactants in each domain becomes small and it strongly fluctuates. This is, in fact, the situation in the interstellar medium, where some crucial reactions take place on the surfaces of microscopic dust grains. In this case rate equations fail and the simulation of surface reactions requires stochastic methods such as the master equation. However, in the case of complex reaction networks, the master equation becomes infeasible because the number of equations proliferates exponentially. To solve this problem, we introduce a stochastic method based on moment equations. In this method the number of equations is dramatically reduced to just one equation for each reactive species and one equation for each reaction. Moreover, the equations can be easily constructed using a diagrammatic approach. We demonstrate the method for a set of astrophysically relevant networks of increasing complexity. It is expected to be applicable in many other contexts in which problems that exhibit analogous structure appear, such as surface catalysis in nanoscale systems, aerosol chemistry in stratospheric clouds, and genetic networks in cells.     

Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics

In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.     

Molecular dynamics with stochastic boundary conditions

We present and illustrate a simple approach for carrying out molecular dynamics simulations subject to stochastic boundary conditions. Methods of this type are expected to be useful in the study of chemical reactions and other localized processes in dense media.     

Soft Matter Approaches for Enhancing the Catalytic Capabilities of Polyoxometalate Clusters

In this minireview, we discuss the recent efforts on expanding the catalytic capabilities of polyoxometalates (POM) through emulsion catalysis approaches with novel catalytic-active POM–organic hybrid clusters as emulsifiers. The hybrid emulsifiers include surfactant encapsulated POM complexes, molecular POMs–organic hybrids, and POM-based solid nanoparticles. With such novel approaches the catalytic efficiency of the POMs can be significantly improved by enhancing the compatibility of the POMs with organic media, providing catalytic interface for biphasic reactions, as well as easier preparation, and better recyclability. Particularly, a simple, green chemistry method to prepare metal nanoparticle materials with POMs as both reducing and capping agents in aqueous is reviewed.     

Nonspecific catalysis by protein surfaces

Catalytic antibodies are the best availablea llaround enzyme mimics. They provide a unique experimental approach and some special insights into general questions about catalysis by enzymes. They offer enantiospecific reactions and levels of substrate binding that compare well with typical enzyme reactions, but not—so far—comparable catalytic efficiency. We and others have used the Kemp elimination as a probe of catalytic efficiency in antibodies. We compare these reactions with nonspecific catalysis by other proteins, and with catalysis by enzymes. Several simple reactions are catalyzed by theserum albumins with Michaelis-Menten kinetics, and can be shown to involve substrate binding and catalysis by local functional groups. Here, we report the details of one investigation, which implicate known binding sites on the protein surface and discuss implications for catalyst design and efficiency.     

Polymer nanocomposite membranes and their application for flow catalysis and photocatalytic degradation of organic pollutants

The modern world essentially needs a chemical industry that can operate with reduced production costs, and produce high-quality products with low environmental impact. The polymer nanocomposite-based flow catalytic membrane reactor where the reaction and separation can be amalgamated in one unit is considered as one of the new alternative solutions to solve these problems. In this review, we have discussed state-of-the-art flow-through catalytic reactors based on polymer nanocomposite membranes. The unique advantages of flow catalysis include uninterrupted operation, good recyclability, and reaction product without contamination that leads to simple purification. Various catalytic model reactions such as coupling, hydrogenation, esterification in the flow system are presented. We have also presented an overview of methods adopted for preparing such nanocomposite membranes. In the last section, a discussion has been made on the recent advances on polymer-based nanocomposite membranes for the degradation and separation of organic pollutants.     

Gas-phase catalysis by atomic and cluster metal ions: the ultimate single-site catalysts

Gas-phase experiments with state-of-the-art techniques of mass spectrometry provide detailed insights into numerous elementary processes. The focus of this Review is on elementary reactions of ions that achieve complete catalytic cycles under thermal conditions. The examples chosen cover aspects of catalysis pertinent to areas as diverse as atmospheric chemistry and surface chemistry. We describe how transfer of oxygen atoms, bond activation, and coupling of fragments can be mediated by atomic or cluster metal ions. In some cases truly unexpected analogies of the idealized gas-phase ion catalysis can be drawn with related chemical transformations in solution or the solid state, and so improve our understanding of the intrinsic operation of a practical catalyst at a strictly molecular level.     

动力学方程控制表面反应的模拟模型和方法

提出了动力学方程控制表面反应的模拟模型和方法.该模型从最基本的质量作用定律出发,获得表面反应的动力学方程.而表面反应通过格子模拟反应器进行.通过表面催化样板反应"CO表面催化氧化"检验了该模拟模型和方法,与实验结果吻合.该模型可在其它复杂的表面催化反应体系中推广应用.     

Abstract Next Subvolume Method: a logical process-based approach for spatial stochastic simulation of chemical reactions

The spatial stochastic simulation of biochemical systems requires significant calculation efforts. Parallel discrete-event simulation is a promising approach to accelerate the execution of simulation runs. However, achievable speedup depends on the parallelism inherent in the model. One of our goals is to explore this degree of parallelism in the Next Subvolume Method type simulations. Therefore we introduce the Abstract Next Subvolume Method, in which we decouple the model representation from the sequential simulation algorithms, and prove that state trajectories generated by its executions statistically accord with those generated by the Next Subvolume Method. The experimental performance analysis shows that optimistic synchronization algorithms, together with careful controls over the speculative execution, are necessary to achieve considerable speedup and scalability in parallel spatial stochastic simulation of chemical reactions. Our proposed method facilitates a flexible incorporation of different synchronization algorithms, and can be used to select the proper synchronization algorithm to achieve the efficient parallel simulation of chemical reactions.     

How hard is mechanism elucidation in catalysis? Combinatorial analysis of C1 chemistry

Most chemical reactions occur over multiple steps whose identity is elucidated by experiment, yielding a reaction mechanism. Knowledge of cognitive science suggests that mechanism elucidation can be viewed as a knowledge-guided search within a combinatorial space. The MECHEM computer program searches this space comprehensively for the simplest plausible mechanisms. We use MECHEM to find mechanisms for Fischer-Tropsch chemistry and CO2 re-forming of methane, both heterogeneous catalytic reactions of current importance. The results reveal hundreds of equally simple mechanisms consistent with evidence. Hence, mechanism elucidation in catalysis is a much harder problem than is ordinarily realized.     

Theoretical Design of Catalytic Domain of Abzyme Se-scFv2F3 by Introducing a Catalytic Triad

The single chain antibody scFv2F3 can be converted into selenium-containing Se-scFv2F3 by chemical mutation of the Ser residues. With antibody fragment 1NQB as a template, the catalytic domain of scFv2F3 was built by using homology modeling and molecular dynamics(MD) simulations. On the basis of the 3D model, we discussed the importance of Ser52 as the chemical modification site and redesigned the protein groups nearby Ser52 via introducing a catalytic triad. The following 10 ns MD results show that the des...     

Eliminating fast reactions in stochastic simulations of biochemical networks: a bistable genetic switch

In many stochastic simulations of biochemical reaction networks, it is desirable to "coarse grain" the reaction set, removing fast reactions while retaining the correct system dynamics. Various coarse-graining methods have been proposed, but it remains unclear which methods are reliable and which reactions can safely be eliminated. We address these issues for a model gene regulatory network that is particularly sensitive to dynamical fluctuations: a bistable genetic switch. We remove protein-DNA and/or protein-protein association-dissociation reactions from the reaction set using various coarse-graining strategies. We determine the effects on the steady-state probability distribution function and on the rate of fluctuation-driven switch flipping transitions. We find that protein-protein interactions may be safely eliminated from the reaction set, but protein-DNA interactions may not. We also find that it is important to use the chemical master equation rather than macroscopic rate equations to compute effective propensity functions for the coarse-grained reactions.     

Hot Electrons at Solid–Liquid Interfaces: A Large Chemoelectric Effect during the Catalytic Decomposition of Hydrogen Peroxide

The study of energy and charge transfer during chemical reactions on metals is of great importance for understanding the phenomena involved in heterogeneous catalysis. Despite extensive studies, very little is known about the nature of hot electrons generated at solid–liquid interfaces. Herein, we report remarkable results showing the detection of hot electrons as a chemicurrent generated at the solid–liquid interface during decomposition of hydrogen peroxide (H₂O₂) catalyzed on Schottky nanodiodes. The chemicurrent reflects the activity of the catalytic reaction and the state of the catalyst in real time. We show that the chemicurrent yield can reach values up to 10^?1 electrons/O₂ molecule, which is notably higher than that for solid–gas reactions on similar nanodiodes.