Project Summary Advances in chemical synthesis provide access to complex biologically active structures that are highly relevant as pharmaceuticals and analysis tools. High performance reactions that allow selective formation of specific covalent bonds are usually achieved by first uncovering their fundamental chemical reaction mechanisms, as these mechanistic details pave the way for further experimentation. Especially in the areas of C-H functionalization, Lewis acid/base chemistries, and stereoselective transformations, the mechanism discovery and characterization are vital due to the high difficultly level in achieving these reaction steps. Advances in this area will enable construction of a wide variety of powerful therapeutics, signaling probes, and natural products. Our ongoing research leverages first principles simulations to greatly accelerate catalyst development for novel synthetic reactions. The Zimmerman group's novel reaction pathway discovery tools are especially well-positioned for this task, being able to reveal unexpected as well as intuitive reaction paths, giving deep insight into the atomistic details of reactivity. In collaboration with numerous reaction development groups, these tools are being used to reveal principles for several classes of catalysts, and have even allowed new catalyst structures to be designed. Application of these methods to the proposed transformations (Ni-based C-H functionalization, macrolide glycosylation by chiral organocatalysts, Lewis-acid catalyzed carbonyl-olefin metathesis, and oxidative enzymatic transformations) is providing the fundamental scientific insight needed to enable challenging synthetic steps. In summary, this research plan uses computational means to design catalysts for highly selective transformations and will enable synthesis of a variety of scientifically and therapeutically relevant molecules, with profound implications for the treatment and study of human health. This supplement will provide necessary computer resources to continue to achieve this task, by acquiring hardware to enable GPU-accelerated quantum chemical algorithms. In sum, this instrumentation will not only replace aging hardware, but also accelerate our research with modern computing architectures, permitting increased productivity of team members and improved collaborative capabilities.