No abstract

The flexibility of double-stranded (ds) RNA and dsDNA is crucial for their biological functions. Recent experiments have shown that the flexibility of dsRNA and dsDNA can be distinctively different in the aspects of stretching and twist-stretch coupling. Although various studies have been performed to understand the flexibility of dsRNA and dsDNA, there is still a lack of deep understanding of the distinctive differences in the flexibility of dsRNA and dsDNA helices as pertains to their stretching and twist-stretch coupling. In this work, we have explored the relative flexibility in stretching and twist-stretch coupling between dsRNA and dsDNA by all-atom molecular dynamics simulations. The calculated stretch modulus and twist-stretch coupling are in good accordance with the existing experiments. Our analyses show that the differences in stretching and twist-stretch coupling between dsRNA and dsDNA helices are mainly attributed to their different (A- and B-form) helical structures. Stronger basepair inclination and slide in dsRNA is responsible for the apparently weaker stretching rigidity versus that of dsDNA, and the opposite twist-stretch coupling for dsRNA and dsDNA is also attributed to the stronger basepair inclination in dsRNA than in dsDNA. Our calculated macroscopic elastic parameters and microscopic analyses are tested and validated by different force fields for both dsRNA and dsDNA.

Knowledge-based statistical potentials have been shown to be efficient in protein structure evaluation/prediction, and the core difference between various statistical potentials is attributed to the choice of reference states. However, for RNA 3D structure evaluation, a comprehensive examination on reference states is still lacking. In this work, we built six statistical potentials based on six reference states widely used in protein structure evaluation, including averaging, quasi-chemical approximation, atom-shuffled, finite-ideal-gas, spherical-noninteracting, and random-walk-chain reference states, and we examined the six reference states against three RNA test sets including six subsets. Our extensive examinations show that, overall, for identifying native structures and ranking decoy structures, the finite-ideal-gas and random-walkchain reference states are slightly superior to others, while for identifying near-native structures, there is only a slight difference between these reference states. Our further analyses show that the performance of a statistical potential is apparently dependent on the quality of the training set. Furthermore, we found that the performance of a statistical potential is closely related to the origin of test sets, and for the three realistic test subsets, the six statistical potentials have overall unsatisfactory performance. This work presents a comprehensive examination on the existing reference states and statistical potentials for RNA 3D structure evaluation.

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions.