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Energy hyperspace for stacking interaction in AU/AU dinucleotide step: Dispersion-corrected density functional theory
Sanchita Mukherjee1, Senthilkumar Kailasam, Manju Bansal
1Biophysics Division, Saha Institute of Nuclear Physics, Kolkata, 700064, India.
This study models DNA and RNA stacking interactions, revealing optimal geometries for base pairs. Incorporating sugar-phosphate backbone constraints improves energy calculations for accurate double helix structure prediction.
Area of Science:
- Structural Biology
- Computational Chemistry
- Biophysics
Background:
- DNA and RNA double helices are primarily shaped by base pair stacking interactions.
- Previous studies on stacking interactions lacked geometric variation, limiting understanding of unusual roll values in RNA.
- Purine-pyrimidine steps typically exhibit small roll values due to sequence-directed features.
Purpose of the Study:
- To generate stacking energy hyperspace by modeling geometric variations (roll and slide) in base pair steps.
- To identify the most suitable quantum chemical methods for analyzing stacked base pair systems.
- To investigate the influence of sugar-phosphate backbone constraints on stacking energy contours.
Main Methods:
- Modeled base pair geometries with variations in roll and slide degrees of freedom.
- Calculated stacking energy contours using various quantum chemical methods, including dispersion corrections (DFT-D).
- Incorporated an energy penalty term for C1'-C1' distance deviations to account for RNA backbone constraints.
Main Results:
- Established reliable quantum chemical methods for stacked base pair analysis, despite computational limitations.
- All methods predicted negative roll and near-zero slide as favorable for purine-pyrimidine steps, aligning with steric clash rules.
- The DFT-D functional ωB97X-D, with a distance-based penalty, accurately predicted energy contours for AU/AU and other purine-pyrimidine steps.
Conclusions:
- The study provides a robust method for calculating stacking energies in nucleic acid double helices.
- Accounting for backbone constraints significantly improves the accuracy of energy contours, especially for specific sequences like AU/AU.
- Findings enhance the understanding of sequence-directed structural features in DNA and RNA double helices.
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