Comparison of Intrinsic Stacking Energies of Ten Unique Dinucleotide Steps in A-RNA and B-DNA Duplexes. Can We Determine Correct Order of Stability by Quantum-Chemical Calculations?

Abstract

High level ab initio methods have been used to study stacking interactions in ten unique base pair steps both in A-RNA and in B-DNA duplexes. The protocol for selection of geometries based on molecular dynamics (MD) simulations is proposed, and its suitability is demonstrated by comparison with stacking in steps at fiber diffraction geometries. It is shown that fiber diffraction geometries are not sufficiently accurate for interaction energy calculations. In addition, the protocol for selection of geometries based on MD simulations allows for the evaluation of the variability of the intrinsic stacking energies along the MD trajectories. The uncertainty in stacking energies (difference between the most and least stable geometry) due to the dynamical nature of systems can be, in some cases, as large as 3.0 kcal · mol, which is almost 50% of the actual sequence dependence of base stacking energies (the energy difference between the most and least stable sequences). Thus, assessing the relative magnitude of the gas phase stacking energy using a single geometry for each sequence is insufficient to obtain an unambiguous order of gas phase stacking energies in canonical double helices. Though the ordering of ten unique dinucleotide steps cannot be definitive, some general conclusions were drawn. The stacking energies of base pair steps in A-RNA are more evenly separated compared to B-DNA, and their ordering is less sensitive to the dynamics of the system compared to be B-DNA. The most stable step both in B-DNA and A-RNA is the CG/CG step that is well separated from the second most stable step GC/GC. Also the least stable step (the CC/GG step) is well separated from the rest of the structures. The calculations further show that B-DNA stacking is favorable only marginally (on average by 1.14 kcal · mol -1 per base pair step) over A-RNA stacking, and this difference vanishes after subtracting the stabilizing van der Waals effect of the thymine 5-methyl group that is absent in RNA. Basically, no correlation between the sequence dependence of gas phase stacking energies and the sequence dependence of ∆G°3 7 free energies used in nearest-neighbor models was found either for B-DNA or for A-RNA. This reflects the complexity of the balance of forces that are responsible for the sequence dependence of thermodynamics stability of nucleic acids, which masks the effect of the intrinsic interactions between the stacked base pairs.

Evaluation of the internal transcribed spacer 2 (ITS2) as a molecular marker for phylogenetic inference using sequence and secondary structure information in blow flies (Diptera: Calliphoridae)

“…T bias in the rDNA region of some Diptera groups (Schlötterer et al 1994;Friedrich and Tautz 1997;Young and Coleman 2004) and by the essential function played by these rDNA molecules in the cell, which relies mostly on the correct structural folding. It is also in agreement with empirical works on RNA/DNA structural thermodynamics, which showed that GC-rich double-stranded helices are more stable than AU rich ones, especially when GC pairs are located near helices ends (Xia et al 1998;Svozil et al 2010).…”

Sequence and conformation effects on ionization potential and charge distribution of homo-nucleobase stacks using M06-2X hybrid density functional theory calculations

“…Indeed, the optimization of stacks in the absence of the sugar-phosphate backbone and the solvent are likely to lead to unphysical structures that may be very different from the standard conformations. Note that another approach developed to select relevant geometries and to monitor their fluctuations is based on molecular dynamics simulations (Svozil, Hobza, & Šponer, 2010). …”

Energy hyperspace for stacking interaction in AU/AU dinucleotide step: Dispersion‐corrected density functional theory study

“…The urge to develop faster quantum chemical procedures for the biomolecular system directed the improvement of density functional theory (DFT), but it was indicated that local as well as semilocal DFT methods cannot describe dispersion interactions properly. [27][28][29] It was shown by our group 27 and others 30 that DFT-D method is most suitable for the estimation of stacking energy as it can predict correct trend of twist values, whereas others fail in such cases. 11 Variations in structural parameters of nucleic acid double helices are often recognized to be sequence dependent.…”

“…10 The advancement of the dispersion-corrected DFT (DFT-D) methodology now allows this potential problem to be addressed in which the dispersion energy is added using the traditional C 6 /R 6 term and it has been tested to give good agreement with the experimental values. Reparameterization of the DFT functional itself in the presence of empirical dispersion correction is being described as most recommended DFT-based methods for noncovalent complexes, 31,32 where some studies lead to quite successful description of individual base-base 33 and base pair step stacking 27,28 in DNA as well as RNA. [12][13][14] A large number of studies have related stacking interactions to variations of these structural parameters.…”