These results establish replica-exchange enhanced sampling, particularly T-REMD, as an effective strategy for constructing experimentally validated RNA ensembles and accessing conformations corresponding to rare functional substates.
Abstract
Accurate determination of RNA conformational ensembles is essential for understanding RNA function and advancing RNA-targeted drug discovery, yet lowly-populated alternative states remain difficult to resolve with atomistic detail. A central constraint is that experimental refinement can only select conformations already present in the starting library, making library generation the limiting step. Using the HIV-1 trans-activation response element (TAR) as a model system, we benchmarked conventional MD (cMD) against the enhanced sampling methods Gaussian-accelerated MD (GaMD), replica-exchange Gaussian-accelerated MD (Rex-GaMD), replica-exchange with solute tempering (REST2), and temperature replica-exchange MD (T-REMD), as well as the structure-prediction based methods FARFAR2 and AlphaFold 3. Each library was refined against experimental residual dipolar couplings (RDC) and validated independently using ensemble-averaged QM/MM chemical shifts. We showed that T-REMD produced the most accurate ensemble by both measures, and its advantage tracked with broader, more continuous coverage of the interhelical conformational landscape. Broad temperature-range T-REMD also sampled conformations resembling excited state 1 (ES1) and the U23-A27-U38 base-triple, without requiring these states to be specified during library generation. More accurate ensembles further improved coverage of experimentally observed ligand-bound TAR conformations and enhanced ensemble-based virtual screening, linking structural accuracy to functional utility. The same workflow applied to the preQ1 class I riboswitch and the UUCG tetraloop improved agreement with experimental data in both cases. Together, these results establish replica-exchange enhanced sampling, particularly T-REMD, as an effective strategy for constructing experimentally validated RNA ensembles and accessing conformations corresponding to rare functional substates. Graphical Abstract
RNA molecules explore heterogeneous conformational ensembles that are essential for their biological function and molecular recognition, yet this intrinsic flexibility poses a major challenge for structure-based drug discovery. In particular, the absence of well-defined binding pockets in static structures limits the i...
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