Studying the dynamical properties of small RNA molecules with computational techniques
Pinamonti, Giovanni
The role of ribonucleic acid (RNA) in molecular biology is shifting from a
mere messenger between DNA (deoxyribonucleic acid) and proteins to an im-
portant player in many cellular activities. The central role of RNA molecules
calls for a precise characterization of their structural and dynamical properties.
Nowadays, experiments can be efficiently complemented by computational ap-
proaches.
This thesis deals with the study of the dynamical properties of small RNA
molecules, exploiting various computational techniques. Specifically we inves-
tigate two different complementary methods, elastic network models (ENMs)
and Markov state models (MSMs).
ENMs are valuable and efficient tools for characterizing the collective inter-
nal dynamics of biomolecules. We evaluate their performance by comparing
their predictions with the results of atomistic molecular dynamics (MD) sim-
ulations and selective 2’-hydroxyl analyzed by primer extension (SHAPE) ex-
periments. We identify the optimal parameters that should be adopted when
putting into use such models.
MSMs are tools that allow to probe long-term molecular kinetics based
on short-time MD simulations. We make use of MSMs and MD simulations
to measure the kinetics and the timescale of the stacking-unstacking motion
for a collection of short RNA oligonucleotides, comparing the results with
previously published relaxation experiments. We then move to the study of
the process of the fraying of the terminal base pair in a helix, characterizing
the different involved pathways and the sequence dependence of the process
timescale.
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