A New Method to Predict Ion Effects in RNA Folding

Abstract

Summary The strong interaction between metal ions in the solution and the highly charged RNA molecule is critical for RNA structure formation and stabilization. Metal ions binding to RNA can induce RNA structural changes that are important for RNA cellular functions. Therefore, quantitative modeling of the ion effects is essential for RNA structure prediction and RNA-based molecular design. Recently, inspired by the increasing experimental evidence that supports the importance of ion correlation and fluctuation in ion-RNA interactions, we developed a new computational model, Monte Carlo Tightly Bound Ion (MCTBI) model. The validity of the model is shown by the improved accuracy in the predictions for ion binding properties and ion-dependent free energies for RNA structures. In this chapter, using homodimeric tetraloop-receptor docking as an illustrative case, we show the MCTBI method for the computational prediction of the ion effects in RNA folding.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

“…Altered ionic conditions change the thermodynamic behavior of RNA molecules, especially in the presence of multivalent ions such as Mg 2þ . Extending folding free-energy calculations to include salt dependence on the basis of experimental data, the previous TBI model (9,(26)(27)(28)(29) and the new Monte Carlo TBI (MCTBI) model (63)(64)(65) both estimate the ion-dependent thermodynamic stability of RNA structures. Additionally, recent studies (66,67) indicate that 3D interactions can influence RNA folding at an early stage in the process, and the emergence of a cooperative 3D interaction network guides the search for the native state.…”