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Using All-Atom Potentials to Refine RNA Structure Predictions of SARS-CoV-2 Stem Loops
Published
Author(s)
Christina Bergonzo, Andrea L. Szakal
Abstract
A considerable amount of rapid-paced research is underway to combat the SARS-CoV-2 11 pandemic. In this work, we assess the 3D structure of the 5' untranslated region of its RNA, in the 12 hopes that stable secondary structures can be targeted, interrupted, or otherwise measured. To this 13 end, we have combined molecular dynamics simulations with previous Nuclear Magnetic 14 Resonance measurements for stem loop 2 of SARS-CoV-1 to refine 3D structure predictions of that 15 stem loop. We find that relatively short sampling times allow for loop rearrangement from predicted 16 structures determined in absence of water or ions, to structures better aligned with experimental 17 data. We then use molecular dynamics to predict the refined structure of the TRS-L region which 18 includes stem loop 3, and show that arrangement of the loop around exchangeable monovalent 19 potassium can interpret the conformational equilibrium determined by in-cell DMS data.
Bergonzo, C.
and Szakal, A.
(2020),
Using All-Atom Potentials to Refine RNA Structure Predictions of SARS-CoV-2 Stem Loops, International Journal of Molecular Sciences, [online], https://doi.org/10.3390/ijms21176188
(Accessed December 6, 2024)