This dissertation details the use of computational methods to understand the effect that cancer-related mutations have on proteins that complex with nucleic acids. Firstly, we perform molecular dynamics (MD) simulations of various mutations in DNA polymerase κ (pol κ). Through an experimental collaboration, we classify the mutations as more or less active than the wild type complex, depending upon the incoming nucleotide triphosphate. From these classifications we use quantum mechanics/molecular mechanics (QM/MM) to explore the reaction mechanism. Preliminary analysis points to a novel method for nucleotide addition in pol κ. Secondly, we study the ten-eleven translocation 2 (TET2) enzyme in various contexts. We find that the identities of both the substrate and complementary strands (or lack thereof) are crucial for maintaining the complex structure. Separately, we find that point mutations within the protein can affect structural features throughout the complex, only at distal sites, or only within the active site. The mutation's position within the complex alone is not indicative of its impact. Thirdly, we share a new method that combines direct coupling analysis and MD to predict potential rescue mutations using poly(ADP-ribose) polymerase 1 as a model enzyme. Fourthly, we perform MD simulations of mutations in the protection of telomeres 1 (POT1) enzyme. The investigated variants modify the POT1-ssDNA complex dynamics and protein—DNA interactions. Fifthly, we investigate the incorporation of remdesivir and other nucleotide analogue prodrugs into the protein-RNA complex of severe acute respiratory syndrome-coronavirus 2 RNA-dependent RNA polymerase. We find evidence for destabilization throughout the complex and differences in inter-subunit communication for most of the incorporation patterns studied. Finally, we share a method for determining a minimum active region for QM/MM simulations. The method is validated using 4-oxalocrotonate, TET2, and DNA polymerase λ as test cases.
