Assessing RNA atomistic force fields via energy landscape explorations in implicit solvent

Predicting the structure and dynamics of RNA molecules still proves challenging because of the relative scarcity of experimental RNA structures on which to train models and the very sensitive nature of RNA towards its environment. In the last decade, several atomistic force fields specifically designed for RNA have been proposed and are commonly used for simulations. However, it is not necessarily clear which force field is the most suitable for a given RNA molecule. In this contribution, we propose the use of the computational energy landscape framework to explore the energy landscape of RNA systems as it can bring complementary information to the more standard approaches of enhanced sampling simulations based on molecular dynamics. We apply the EL framework to the study of a small RNA pseudoknot, the Aquifex aeolicus tmRNA pseudoknot PK1, and we compare the results of five different RNA force fields currently available in the AMBER simulation software, in implicit solvent. With this computational approach, we can not only compare the predicted 'native' states for the different force fields, but the method enables us to study metastable states as well. As a result, our comparison not only looks at structural features of low energy folded structures, but provides insight into folding pathways and higher energy excited states, opening to the possibility of assessing the validity of force fields also based on kinetics and experiments providing information on metastable and unfolded states.

The online version contains supplementary material available at 10.1007/s12551-024-01202-9.