Methods Development in Quantum Mechanics and Molecular Mechanics for Drug Discovery

Computational methods have the potential to significantly reduce the cost of drug discovery by providing key target-specific structural and physics-based information to guide the process of identifying and optimizing lead compounds. This dissertation will present developments in two classes of methods, each with a distinct balance of computational cost and accuracy. In the first part of this work, developments in the DFT-LOC methodology will be presented. The DFT-LOC methodology is successfully extended to the challenging problem of transition metal pKa prediction using a series of first-row hexaaqua complexes inspired by Photosystem II. The results of a second study involving the calculation of barrier heights in C-H bond activations in Cytochrome P450 and Methane Monooxyenase using QM/MM are presented. Dispersion corrections are combined with LOC corrections in order to achieve good agreement with experiment. In the second part of this dissertation, developments in molecular docking and protein structure prediction are discussed. The development of a novel algorithm for treating interloop interactions in proteins will be presented in the context of the Protein Local Optimization Program (PLOP). Finally, the details of a next-generation scoring function, called WSCORE, for molecular docking is presented along with application to MCL-1.