FRET-guided integrative modeling resolves Mg2+-dependent RNA tertiary-contact formation

Inside every living cell, complex machines built from RNA molecules perform the essential work of reading genetic instructions and building proteins. To function correctly, these long, floppy strands must fold into precise three-dimensional shapes, much like a piece of origami that must hold its form to be useful. A critical part of this folding process involves specific sections of the RNA strand reaching out to grab onto other sections, locking the structure into place. These connections, known as tertiary contacts, are often stabilized by magnesium ions, which act as a kind of molecular glue. While scientists have long been able to take high-resolution photographs of these folded structures, such images typically capture only a single, frozen moment in time. This static view can be misleading, as it fails to show the full range of movements and shapes the molecule adopts while floating in the fluid environment of a cell, where it constantly shifts and breathes.

To understand how these RNA structures behave in reality, researchers turned to a technique called single-molecule fluorescence resonance energy transfer, or smFRET. This method acts like a molecular ruler, allowing scientists to measure the distance between two specific points on a single RNA strand as it moves. By watching these distances change, they can see the different shapes a molecule takes on and how often it switches between them. In this new study, the team focused on a specific and common RNA motif where a four-letter sequence, known as a tetraloop, connects with a receptor loop to stabilize the fold. They wanted to know exactly how magnesium ions influence this connection and whether the molecule exists in a single locked shape or a mixture of different forms depending on the salt conditions around it.

The researchers constructed a simplified model of this RNA interaction, linking the two key parts with a flexible tail to mimic the natural freedom of movement found in larger molecules. They then used powerful computer simulations to build a detailed, atom-by-atom picture of how this model behaves. To ensure their computer models were accurate, they compared their virtual results against real-world experiments. They measured the actual distances between the RNA parts in a lab under different salt conditions and used those measurements to guide and refine their simulations. This approach, known as integrative modeling, allowed them to combine the precision of computer physics with the reality of experimental data to create a dynamic picture of the RNA in action.

The results revealed a surprising complexity in how these molecules behave. When the researchers simulated the RNA in an environment with very high concentrations of magnesium, far higher than what is found in a normal cell, the model showed the RNA locking tightly into a single, stable shape that matched the static images seen in previous studies. However, when they adjusted the simulation to match a more realistic concentration of 10 millimolar magnesium, the picture changed completely. Under these intermediate conditions, the RNA did not settle into one rigid form. Instead, the simulations showed a heterogeneous mixture where the molecule constantly switched between a bound state, where the loops were connected, and an unbound state, where they were separated. This dynamic behavior was confirmed by the experimental data, which showed a spread of distances rather than a single fixed point.

This finding challenges the idea that these RNA structures exist in just one permanent shape. The study demonstrates that at physiologically relevant magnesium levels, the molecule is not static but rather exists as a shifting population of different conformations. The researchers found that only by using their integrative approach, which combined computer modeling with single-molecule measurements, could they detect these invisible subpopulations. Static high-resolution structures and traditional ensemble measurements had missed this nuance, presenting a simplified view that did not reflect the true, fluid nature of the molecule in solution. By resolving these hidden states, the work provides a clearer path for validating and refining our understanding of how RNA folds and functions within the complex chemical environment of a living cell.