Multiscale modeling in nanostructures: Physical and biological systems

With the advent of more powerful computer systems, theoretical modeling of nanoscale systems has quickly become a vital part of scientific research in a multitude of disciplines. From the understanding of semiconductor devices to describing the mechanistic details of protein interactions, theoretical studies on systems of various scales have provided great insight into how nature behaves in each scenario. While at a macroscopic level the differences between biological and non-biological systems are apparent, the underlying principles that dictate their behavior are quite similar. Indeed, modeling these two distinct classes of systems have similar challenges. In both cases, the system sizes typically correspond to nanometer length scales and due to the lack of periodicity in the system, one needs to study a relatively larger number of atoms in simulations in order to represent their behavior. Nonetheless, systems that are much smaller than what exists in experiment may be used to describe specific properties of interest, such as how system stability scales with varying size or describing a reaction process of a large biological structure through the modeling of only the reaction site and not the entire protein. Thus, it is important to be able to correctly and efficiently model various systems at multiple scales in order to provide proper insight and understanding so models and tools developed in one area could be applied to another discipline. Indeed, lessons learned during the process are quite valuable for the general scheme of multiscale modeling in materials. To facilitate this, we have investigated two separate cases involving the efficient use of multiscale modeling through ab initio density functional theory calculations.;For the first half of this work, we investigate the effect of size on the net magnetization of zero dimensional graphene based structures with differing edge states. Currently, we have shown that for zigzag edged triangular graphene structures, we find that the net ferrimagnetization increases linearly with size. Conversely for armchair edged structures, we find that the net magnetization remains in a degenerate non-magnetic/anti-ferromagnetic state with zero net magnetization. From here, we investigated the effect on the net magnetization and band gap of the zigzag edged structures when the system size increases into the nanometer range. We see that there is a consistent increase in the net magnetization of the zigzag edged structures as the overall size increases, while simultaneously there is a noticeable decrease in the band gap. Concluding the section on graphene based structures, we examine the optical properties of graphene. Specifically, we examined the transmission of light through graphene in the optical spectrum as a function of lattice spacing, the number of layers, and the position of the layers with respect to one another.;For the second half of this work, we move to a biological context in which we studied the effect of specific mutations in a protein. We find that in the context of the DnaE intein, mutations to the Thr69 residue can alter the conformational arrangement of the Gly-1 residue of the neighboring catalytic Cys1. We find that through hydrogen bonding, Gly-1 may adopt a distorted conformation which alters the splicing rate of the intein. We find that with the presence of Thr69 and the distorted Gly-1 conformation, the reaction barrier is less than that of the case with Thr69 mutated to Ala69 and a non-distorted conformation in Gly-1, which is supported by experimental data. Expanding our study on controlling the splicing mechanism, we examine the effect of metals on the N-S acyl shift. We find that by introducing even a single metallic ion near the reaction site of intein splicing, there are large differences in the reaction barriers. Furthermore, we find that due to a lack of pi backbonding, certain metals such as platinum can in fact reduce the reaction barrier of the N-S acyl shift, thus accelerating the intein splicing process at the macroscopic scale.