Organometallic reactions are a fundamental class of chemical transformations. The mechanisms of organometallic reactions are routinely modeled by calculating intermediates and transition-state structures on a potential energy surface with density functional theory (DFT). The translation of these calculated structures to a reaction mechanism is typically done under the umbrella of statistical transition state theory. This dissertation reports the use of DFT calculations and quasiclassical direct dynamics trajectories to explore the possibility of nonstatistical dynamic effects in organometallic reactions. Chapter 1 provides a brief review of potential energy surfaces, transition state theory, dynamics trajectories, and a review of previous dynamics studies of organometallic reactions. Chapter 2 reports dynamics trajectories of an organometallic β–hydride transfer reaction with Rh, Ir, and Co metal centers. This chapter was previously published as Dalton Trans. 2020, 49, 7747-7757. Chapters 3 reports the potential energy surface and structures for benzene reductive elimination for dimethyl silyl-bridged W and Mo metallocene complexes. Chapter 4 reports gas-phase and explicit solvent dynamics trajectories for this benzene reductive elimination reaction.

Atomistic modeling and simulation methods enable a modern molecular approach to bio-medical research. Issues addressed range from structure-function relationships to structure-based drug design. The ability of these methods to address biologically relevant problems is largely determined by their accurate treatment of electrostatic interactions in the target biomolecular structure. In practical molecular simulations, the electrostatic charge density of molecules is approximated by an arrangement of fractional "point charges" throughout the molecule. While chemically intuitive and straightforward in technical implementation, models based exclusively on atom-centered charge placement, a major workhorse of the biomolecular simulations, do not necessarily provide a sufficiently detailed description of the molecular electrostatic potentials for small systems, and can become prohibitively expensive for large systems with thousands to millions of atoms. In this work, we propose a rigorous and generally applicable approach, Optimal Point Charge Approximation (OPCA), for approximating electrostatic charge distributions of biomolecules with a small number of point charges to best represent the underlying electrostatic potential, regardless of the distance to the charge distribution. OPCA places a given number of point charges so that the lowest order multipole moments of the reference charge distribution are optimally reproduced. We provide a general framework for calculating OPCAs to any order, and introduce closed-form analytical expressions for the 1-charge, 2-charge and 3-charge OPCA. We demonstrate the advantage of OPCA by applying it to a wide range of biomolecules of varied sizes. We use the concept of OPCA to develop a different, novel approach of constructing accurate and simple point charge water models. The proposed approach permits a virtually exhaustive search for optimal model parameters in the sub-space most relevant to electrostatic properties of the water molecule in liquid phase. A novel rigid 4-point Optimal Point Charge (OPC) water model constructed based on the new approach is substantially more accurate than commonly used models in terms of bulk water properties, and delivers critical accuracy improvement in practical atomistic simulations, such as RNA simulations, protein folding, protein-ligand binding and small molecule hydration. We also apply our new approach to construct a 3-point version of the Optimal Point Charge water model, referred to as OPC3. OPCA can be employed to represent large charge distributions with only a few point charges. We use this capability of OPCA to develop a multi-scale, yet fully atomistic, generalized Born approach (GB-HCPO) that can deliver up to 2 orders of magnitude speedup compared to the reference MD simulation. As a practical demonstration, we exploit the new multi-scale approach to gain insight into the structure of million-atom 30-nm chromatin fiber. Our results suggest important structural details consistent with experiment: the linker DNA fills the core region and the H3 histone tails interact with the linker DNA. OPC, OPC3 and GB-HCPO are implemented in AMBER molecular dynamics software package. / Ph. D.