Machine Learning on a Quantum Hamiltonian shows that DNA is Much Stretchier than Classical Simulations Suggest

The free energy to pull apart stacked DNA bases is found to be much lower than classical simulations to date have suggested. Thermodynamic calculations are made in explicit water using a machine learning molecular dynamics method, trained on a novel dataset of quantum calculations making an advanced treatment of dispersion interactions. While the novel results contrast with previous classical simulations, they are consistent with values extrapolated down to the nanoscale from single molecule pulling experiments on large DNA double helices. The presented machine learned Hamiltonian for DNA is generally applicable to nucleic acids and is efficient to apply, therefore suggesting wide application in the future.