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Conformational Ensembles from Experimental Data
and Computer Simulations
Poster Abstracts
42
9-POS
Board 9
Refining Molecular Dynamics Simulations of RNA Using Solution NMR Data
Andrea Cesari
, Alejandro Gil Ley, Giovanni Bussi.
SISSA, Trieste, Italy.
RNA structure and dynamics play a fundamental role in non-coding RNAs and significantly
affect functions such as gene expression inhibition, splicing, and catalysis. Molecular dynamics
is a computational tool that can be in principle used to investigate RNA structure and dynamics
at atomistic resolution. However, its capability to predict and explain experimental data is
limited by the accuracy of the employed potential energy functions, also known as force fields.
Recent works have shown that state-of-the-art force fields could predict unphysical
conformations that are not in agreement with experiments. The emerging strategy to overcome
these limitations is to complement molecular dynamics with experimental data included as
restraints. Solution NMR data are particularly useful since they provide averages over the
conformations explored on the experimental time scale and ultimately give access to RNA
dynamics. We here propose a scheme based on the maximum entropy principle to combine bulk
experiments with molecular dynamics simulations explicitly taking into account experimental
errors[1]. This scheme allows to generate conformational ensembles based on a standard force
field, that is used as a prior, and in agreement with experimental data. In addition, the method
can be extended to adjust force fields in a chemically-consistent manner allowing transferable
corrections to be obtained. The resulting RNA force field is then validated on a number of
noncanonical structures.
References
[1] Andrea Cesari, Alejandro Gil-Ley, and Giovanni Bussi. Combining simulations and solution
experiments as a paradigm for RNA force field refinement. J Chem Theory Comput,
12(12):6192–6200, dec 2016.