A coarse-grained model with implicit salt for RNAs: predicting 3D structure, stability and salt effect

TL;DR

This paper introduces a coarse-grained computational model with implicit salt to accurately predict RNA 3D structures, stability, and salt effects across various conditions, addressing limitations of previous models.

Contribution

The novel model incorporates implicit salt effects and thermodynamic conditions, enabling more accurate RNA structure and stability predictions beyond room temperature.

Findings

Successfully folded 46 RNAs with RMSD of 3.5 Å

Predicted melting temperatures with ~1°C deviation

Provided ensemble structures under different salt and temperature conditions

Abstract

To bridge the gap between the sequences and 3-dimensional (3D) structures of RNAs, some computational models have been proposed for predicting RNA 3D structures. However, the existed models seldom consider the conditions departing from the room/body temperature and high salt (1M NaCl), and thus generally hardly predict the thermodynamics and salt effect. In this study, we propose a coarse-grained model with implicit salt for RNAs to predict 3D structures, stability and salt effect. Combined with Monte Carlo simulated annealing algorithm and a coarse-grained force field, the model folds 46 tested RNAs (less than or equal to 45 nt) including pseudoknots into their native-like structures from their sequences, with an overall mean RMSD of 3.5 {\AA} and an overall minimum RMSD of 1.9 {\AA} from the experimental structures. For 30 RNA hairpins, the present model also gives the reliable predictions for the stability and salt effect with the mean deviation ~ 1.0 degrees Celsius of melting temperatures, as compared with the extensive experimental data. In addition, the model could provide the ensemble of possible 3D structures for a short RNA at a given temperature/salt condition.