Stability of proteins involved in major DNA repair mechanisms using Computational Power
Disciplines
Bioinformatics | Biotechnology | Computational Biology | Computer Sciences
Abstract (300 words maximum)
DNA repair mechanisms are critical in maintaining genetic stability, with spontaneous mutations occurring between 10^5 and 10^8 times daily due to endogenous and exogenous factors. This research focuses on three primary DNA repair pathways: Mismatch Repair (MMR), Base Excision Repair (BER), and Double-Strand Break Repair (DSBR), each involving various enzymes that recognize and correct DNA damage. The study investigates the stability of seven DNA repair enzymes through molecular dynamics simulations to calculate their potential and kinetic energies, using Python-based tools and PDB models. Enzyme models were categorized by their DNA repair function, and simulations were run using the OpenMM platform to compute energy profiles over a total of 4 nanoseconds. The binding affinities of five enzyme models were also calculated using PyDockDNA, further assessing the attraction forces between enzymes and DNA. Results show that thymine DNA glycosylase (PDB ID: 3UO7) had the highest stability based on potential energy, while polymerase Mu (PDB ID: 2HTF) exhibited the lowest energy totals, indicating greater flexibility. Additionally, a trend was observed between the number of atoms in the enzyme models and the total energy output, with an exception noted for endonuclease-8 (PDB ID: 2OPF). These findings provide insight into the structural stability and DNA interaction strength of repair enzymes, offering potential applications in cancer treatment strategies by better understanding enzyme behavior during DNA repair.
Academic department under which the project should be listed
CCSE - Information Technology
Primary Investigator (PI) Name
Chloe Yixin Xie
Stability of proteins involved in major DNA repair mechanisms using Computational Power
DNA repair mechanisms are critical in maintaining genetic stability, with spontaneous mutations occurring between 10^5 and 10^8 times daily due to endogenous and exogenous factors. This research focuses on three primary DNA repair pathways: Mismatch Repair (MMR), Base Excision Repair (BER), and Double-Strand Break Repair (DSBR), each involving various enzymes that recognize and correct DNA damage. The study investigates the stability of seven DNA repair enzymes through molecular dynamics simulations to calculate their potential and kinetic energies, using Python-based tools and PDB models. Enzyme models were categorized by their DNA repair function, and simulations were run using the OpenMM platform to compute energy profiles over a total of 4 nanoseconds. The binding affinities of five enzyme models were also calculated using PyDockDNA, further assessing the attraction forces between enzymes and DNA. Results show that thymine DNA glycosylase (PDB ID: 3UO7) had the highest stability based on potential energy, while polymerase Mu (PDB ID: 2HTF) exhibited the lowest energy totals, indicating greater flexibility. Additionally, a trend was observed between the number of atoms in the enzyme models and the total energy output, with an exception noted for endonuclease-8 (PDB ID: 2OPF). These findings provide insight into the structural stability and DNA interaction strength of repair enzymes, offering potential applications in cancer treatment strategies by better understanding enzyme behavior during DNA repair.