Reparameterization of RNA χ Torsion Parameters for the AMBER Force Field and Comparison to NMR Spectra for Cytidine and Uridine

A reparameterization of the torsional parameters for the glycosidic dihedral angle, χ, for the AMBER99 force field in RNA nucleosides is used to provide a modified force field, AMBER99χ. Molecular dynamics simulations of cytidine, uridine, adenosine, and guanosine in aqueous solution using the AMBER99 and AMBER99χ force fields are compared with NMR results. For each nucleoside and force field, 10 individual molecular dynamics simulations of 30 ns each were run. For cytidine with AMBER99χ force field, each molecular dynamics simulation time was extended to 120 ns for convergence purposes. Nuclear magnetic resonance (NMR) spectroscopy, including one-dimensional (1D) 1H, steady-state 1D 1H nuclear Overhauser effect (NOE), and transient 1D 1H NOE, was used to determine the sugar puckering and preferred base orientation with respect to the ribose of cytidine and uridine. The AMBER99 force field overestimates the population of syn conformations of the base orientation and of C2′-endo sugar puckering of the pyrimidines, while the AMBER99χ force field’s predictions are more consistent with NMR results. Moreover, the AMBER99 force field prefers high anti conformations with glycosidic dihedral angles around 310° for the base orientation of purines. The AMBER99χ force field prefers anti conformations around 185°, which is more consistent with the quantum mechanical calculations and known 3D structures of folded ribonucleic acids (RNAs). Evidently, the AMBER99χ force field predicts the structural characteristics of ribonucleosides better than the AMBER99 force field and should improve structural and thermodynamic predictions of RNA structures

Systematic development of predictive molecular models of high surface area activated carbons for the simulation of multi-component adsorption processes related to carbon capture

Adsorption in porous materials is a promising technology for CO2 capture and storage. Particularly important applications are adsorption separation of streams associated with the fossil fuel power plants operation, as well as natural gas sweetening. High surface area activated carbons are a promising family of materials for these applications, especially in the high pressure regimes. As the streams under consideration are generally multi-component mixtures, development and optimization of adsorption processes for their separation would substantially benefit from predictive simulation models. In this project we combine experimental data and molecular simulations to systematically develop a model for a high surface area carbon material, taking activated carbon Maxsorb MSC-30 as a reference. Our study starts from the application of the well-established slit pore model, and then evolves through the development of a more realistic model, based on a random packing of small graphitic fragments. In the construction of the model, we introduce a number of constraints, such as the value of the accessible surface area, concentration of the surface groups and pore volume, to bring the properties of the model structure close to the reference porous material. Once a plausible model is developed, its properties are further tuned through comparison between simulated and experimental results for carbon dioxide and methane. The model is then validated by predictions for the same species at different conditions and by prediction of other species involved in the carbon capture processes. The model is applied to simulate the separations involved in pre and post combustion capture processes and sweetening of sour natural gas, using realistic conditions and compositions for the multicomponent mixtures. Finally, it is used to explore the effect of water in pre and post combustion separations