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Improved Parameterization of Protein-DNA Interactions for Molecular Dynamics Simulations of PCNA Diffusion on DNA.

Seonju YouHong-Guen LeeKimoon KimJejoong Yoo
Published in: Journal of chemical theory and computation (2020)
As the field of molecular dynamics simulation utilizing the force fields is moving toward more complex systems, the accuracy of intermolecular interactions has become a central issue of the field. Here, we quantitatively evaluate the accuracy of the protein-DNA interactions in AMBER and CHARMM force fields by comparing experimental and simulated diffusion coefficients of proliferating cell nuclear antigen. We find that both force fields underestimate diffusion coefficients by at least an order of magnitude because the interactions between basic amino acids and DNA phosphate groups are too attractive. Then, we propose Lennard-Jones parameters optimized using the experimental osmotic pressure data of model chemicals, by using which one can reproduce the experimental diffusion coefficients. Newly optimized parameters will have a broad impact on general protein-DNA interactions.
Keyphrases
  • molecular dynamics simulations
  • single molecule
  • circulating tumor
  • cell free
  • amino acid
  • molecular docking
  • circulating tumor cells
  • machine learning
  • mesenchymal stem cells
  • big data