Abstract: Computational methods have only been applied to large biomolecular systems such as proteins in recent decades due to increases in computer power. The accuracy of such applications is only now being established. Chapter 1 is a quantum mechanical study of orotidine-5'-monophosphate decarboxylase (ODCase), one of the most proficient enzymes known. Despite dozens of experimental and computational studies, the definitive mechanism remains unknown. The reaction energetics for several mechanisms were calculated with quantum mechanical DFT methods using small model systems. The results revealed that all the mechanisms we looked at were favored over the direct mechanism. The Michael addition of acetic acid and Schiff base formation with methylamine had the most favorable energy of formation. In Chapter 2, a more sophisticated method involving quantum mechanical/molecular mechanical (QM/MM) dynamics and metadynamics was used to calculate the free energy barrier for the most popular mechanism, direct decarboxylation, in the enzyme and solution. The results of this study do not support this enzyme mechanism. Chapter 3 is a continuation of this work using the same methodology, but exploring several other mechanisms. This work is currently ongoing. Chapter 4 is a benchmark study for the QM/MM method using the well-characterized reaction catalyzed by chorismate mutase. The barrier to reaction was successfully predicted to within 1.2 kcal/mol. The results also support transition state stabilization by the enzyme. Chapter 5 is a benchmark study of recent pK_a prediction methods. Two methods in particular were tested and compared to values found in the literature for several other methods. PROPKA is a fast empirical method, and was found to have an equal rootmean-square-deviation (RMSD) as another much slower molecular dynamics-based method, termed molecular dynamics/generalized-Born/thermodynamics integration (MD/GB/TI). Both were also found to have high maximum deviations. Addition of explicit waters to the MD/GB/TI simulations did reduce the maximum deviation for this method.