Although many CG representations are available for the most common biomacromolecules, very few have been reported for nucleic acids. Our CG model for DNA maps the complexity of each nucleotide onto six effective superatoms keeping the “chemical sense” of specific Watson-Crick recognition, the phosphate backbone and 5’ – 3’ polarity.
The model includes explicitly electrostatics interactions either under the framework of the generalized Born approach or PME, using a CG model for water developed in our group.
This CG representation is able to accurately reproduce experimental structures, breathing dynamics, and conformational transitions from the A to the B form in double helical fragments.
The model achieves a good qualitative reproduction of temperature-driven melting and its dependence on size, ionic strength, and sequence specificity.
Reconstruction of atomistic models from CG trajectories (backmapping) gives a remarkable agreement with structural, dynamic, and energetic features obtained from fully atomistic simulation, opening the possibility to acquire nearly atomic detail data from CG trajectories. (see more in Dans et al 6 (5), pp 1711. 2010, JCTC)
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