Journal of Theoretical and Computational Chemistry

Possible causal connections between the dynamics of a thermally fluctuating model enzyme molecule and catalysis are explored. The model is motivated by observations from experiment and simulation that amino acid residues residing in different enzymatic domains may show markedly different degrees of conformational freedom. Consequently, we are interested in the catalytic efficacy of an enzyme as a function of long-range many-atom cooperative effects resulting from strong, moderate, and weak interactions between enzymatic residues. Here we show and quantify through molecular dynamics simulations how the number and distribution of these interactions affects an enzyme's conformational fluctuation dynamics and its effectiveness as a catalyst. For any given distribution of "stiff" and "loose" enzymatic domains, catalytic fitness is defined as the number of chemical events — specifically the number of times a catalytic residue and substrate surmount a chemical reaction barrier — during molecular dynamics simulation. Through mutation, recombination, and a selection procedure following the ideas of Darwinian evolution, a genetic algorithm drives a population of enzyme molecules to greater catalytic fitness by modifying the mix of stiff and loose interactions. Approximately 30,000 different enzyme molecules are generated by the genetic algorithm — each with a unique number and distribution of strong, moderate, and weak inter-residue interactions. While the catalytically least fit enzyme exhibits 16 chemical events, the fittest boasts 253. That point mutations far from the active-site chemistry in the fittest enzyme have a strong effect on the number of chemical events suggests that catalysis depends, in part, on long-range many-atom globally correlated dynamical fluctuations.

For estimating log P values of a group of organic compounds, a back-propagation neural network with a 9–6–1 architecture was developed with optimal learning rate (ε) and momentum (μ) of 0.24 and 0.82, respectively. A collection of 131 organic compounds was chosen as data set that consists of normal hydrocarbons, alcohols, ethers, amines, ketones, acids, benzene derivatives, phenols, and aldehydes. The data set was divided into a training set consisting of 118 molecules and a prediction set consisting of 18 molecules. The most important properties that affect the partition coefficients of organic compounds (surface/volume, dipole moment, and those which are related to electrostatic potentials such as the sum of charges on the carbon atoms) were used as descriptors. These descriptors were obtained using AM1 semiempirical MO method for the gas phase geometries. The descriptors were selected via developing a multiple linear regression analysis. The ANN calculated values of partition coefficients (log Ps) for molecules of the training and prediction sets are in good agreement with the experimental values.

With the help of the ab initio method of the full potential linearized augmented-plan-wave, electronic band structure and its magnetic property for a charge transfer compound of bis (ethylenediselena)-tetrathiafulvalene (BEST) with [Fe(CN)₅NO] anions are studied, where the exchange-correlation effects of electrons are accounted. The partial density of states and atomic spin magnetic moments are calculated and discussed. It is found that the π-electron of the iron atom in the t_2g orbital mainly provides the magnetism. Because of the hybridization between oxygen and nitrogen, unpaired electrons localized at the nitric oxide radical contribute the magnetism to the compound. In particular, the calculations of spin magnetic moments reveal that the spin population (spin up and down) of C/Se/S altered in the organic donors, which may lead to antiferromagnetic exchange interactions. We also found that the π-electrons of the 2p-orbital of oxygen, the 2p-orbital of nitrogen, the t_2g-orbital of iron, the 2p-orbital of selenium and the 2p-orbital of sulfur contribute to conductivity. These result reveal that the magnetism and conductivity are coexist in the titled compound. Our results are in good agreement with the experiment.

In this paper, a mixed quantum-classical semi-rigid vibrating rotor target (QC-SVRT) model has been applied to study the reaction O(³P) + CH₄ → CH₃ + OH based on H + CH₄ potential surface of Jordan and Gilbert. In this approach, the relative translational motion between atom and polyatom molecules is treated classically while the others are treated quantum mechanically. The reaction probabilities and rate constants were carried out using the QC-SVRT approach. It was found that the QC-SVRT results are in good agreement with the quantum results and the reaction threshold is correctly produced in the present calculation. The application of this QC-SVRT approach makes it more practical to extend quantum reaction dynamics calculation to larger molecules and more complex systems without incurring significant loss of important quantum effects.

We report a theoretical study of the cyclopropanation reactions of EtZnCHI, (EtZn)₂CH EtZnCHZnI, and EtZnCIZnI radicals with ethylene. The mono-zinc and gem-dizinc radical carbenoids can undergo cyclopropanation reactions with ethylene via a two-step reaction mechanism similar to that previously reported for the CH₂I and IZnCH₂ radicals. The barrier for the second reaction step (ring closure) was found to be highly dependent on the leaving group of the cyclopropanation reaction. In some cases, the (di)zinc carbenoid radical undergoes cyclopropanation via a low barrier of about 5–7 kcal/mol on the second reaction step and this is lower than the CH₂I radical reaction which has a barrier of about 13.5 kcal/mol for the second reaction step. Our results suggest that in some cases, zinc radical carbenoid species have cyclopropanation reaction barriers that can be competitive with their related molecular Simmons-Smith carbenoid species reactions and produce somewhat different cyclopropanated products and leaving groups.

Diffusion coefficients for four equimolar binary gaseous mixtures of NO–noble gases are determined from the principle of corresponding states of viscosity by the inversion technique. The Lennard–Jones 12-6 (LJ 12-6) potential energy function is used as the initial model potential required by the technique. The interaction potential energies from the inversion procedure reproduce diffusion coefficients within 5%.

The reaction path is an important concept in theoretical chemistry. We discuss different definitions, their merits as well as their drawbacks: IRC (steepest descent from saddle), reduced gradient following (RGF), gradient extremals, and some others. Many properties and problems are explained by two-dimensional figures. This paper is both a review and a pointer to future research. The branching points of RGF curves are valley-ridge inflection (VRI) points of the potential energy surface. These points may serve as indicators for bifurcations of the reaction path. The VRI points are calculated with the help of Branin's method. All the important features of the potential energy surface are independent of the coordinate system. Besides the theoretical definitions, we also discuss the numerical use of the methods.

Within a differential expression of the Heisenberg operator, the forward and backward evolution can be joined together along a closed time contour. This manipulation leads to a dramatic cancellation of oscillations due to the two individual propagators in the Heisenberg operator and the resulting forward-backward propagator is more tractable to semiclassical approximations. This article gives a detailed description of the forward-backward semiclassical dynamics (FBSD) formalism. The semiclassical propagators, especially those of the initial value representations (IVRs), are briefly discussed. The derivation of the FBSD based on the Herman–Kluk propagator is reviewed. Different FBSD formulations with other semiclassical IVRs are worked out and numerical calculations show that they are also capable of describing quantum dynamics semiquantitatively and all display accuracy similar to the classical Wigner method.

The modelling of nanoelectronic systems has been the topic of ever increasing activity for nearly two decades. Yet, new questions, challenges and opportunities continue to emerge. In this article we review theoretical and numerical work on two new developments in the theory of molecular-scale electronics. First we review a density functional theory analysis within the Keldysh non-equilibrium Green function formalism to predict nonlinear charge transport properties of nanoelectronic devices. Next we review a recently developed quantum mechanical formalism of current-triggered nuclear dynamics. Finally we combine these theories to describe from first principles the inelastic current and the consequent molecular dynamics in molecular heterojunctions.

The quantum master equation approach involving a weak exciton-phonon coupling is applied to the exciton migration dynamics of dendritic molecular aggregates modeled after a phenylacetylene dendrimer, D25, which exhibits an efficient light-harvesting property. The mechanism of efficient exciton migration from the periphery to the core is studied by analyzing relaxation terms among the exciton states originating in weak exciton-phonon coupling. Partial overlaps of exciton distributions between neighboring exciton states are found to be important for realizing the unique migration behavior by step-by-step transfer from the periphery to the core via multi-step exciton states. The same calculation method is applied to the exciton dynamics of a larger dendritic aggregate model, D127, modeled after the largest synthesized phenylacetylene dendrimer D127 in order to examine the dependencies of the exciton migration on the strength of the intermolecular interaction and the temperature of phonon bath. In the case of the relatively weak dipole-dipole coupling, exciton is not observed to migrate efficiently from the periphery to the core, while the largest exciton population is found to remain in the intermediate generations. This is ascribed to the fact that the thermal excitation to the higher exciton states significantly contributes to the exciton distribution in the equilibrium state when the weak intermolecular interaction reduces the energy difference between exciton states. This indicates that the intermolecular interaction is important not only for the overlaps of the exciton distributions between the exciton states, but also the relation between the exciton energy differences and thermal excitations, which spoil the distinct concentration of exciton distribution in the core generation. In the case of a low temperature, even if the intermolecular interaction is weak, the exciton population in the core region is found to be the largest in all the generations. This suggests that exciton tends to efficiently migrate from the periphery to the core when the temperature is sufficiently low. Implications of these theoretical results are discussed in relation to design of magneto-optical materials and other technological applications.