Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data and Computer Simulations

Poster Abstracts

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.

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