Using All-Atom Potentials to Refine RNA Structure Predictions of SARS-CoV-2 Stem Loops

A considerable amount of rapid-paced research is underway to combat the SARS-CoV-2 pandemic. In this work, we assess the 3D structure of the 5 ' untranslated region of its RNA, in the hopes that stable secondary structures can be targeted, interrupted, or otherwise measured. To this end, we have combined molecular dynamics simulations with previous Nuclear Magnetic Resonance measurements for stem loop 2 of SARS-CoV-1 to refine 3D structure predictions of that stem loop. We find that relatively short sampling times allow for loop rearrangement from predicted structures determined in absence of water or ions, to structures better aligned with experimental data. We then use molecular dynamics to predict the refined structure of the transcription regulatory leader sequence (TRS-L) region which includes stem loop 3, and show that arrangement of the loop around exchangeable monovalent potassium can interpret the conformational equilibrium determined by in-cell dimethyl sulfate (DMS) data.