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SimRNA: a coarse-grained method for RNA 3D structure modeling - new ideas accounting for on non-canonical base pairing Boniecki, Michał


The molecules of the ribonucleic acid (RNA) perform a variety of vital roles in all living cells. Their biological function depends on their structure and dynamics, both of which are difficult to experimentally determine but can be theoretically inferred based on the RNA sequence. SimRNA [1] is one of the computational methods for molecular simulations of RNA 3D structure formation. The method is based on a simplified (coarse-grained) representation of nucleotide chains, a statistically derived model of interactions (statistical potential), and the Monte Carlo method as a conformational sampling scheme. In SimRNA, the backbone of the RNA chain is represented by two atoms per nucleotide, whereas nucleotide bases are represented by three atoms each. In fact, these three atoms are used to calculate a system of local coordinates that allows for positioning of a 3D grid - the actual representation of the base. The 3D grid contains information about the interactions of the entire base moiety (not only the three atoms explicitly included in the SimRNA representation). The current version of SimRNA (3.22) is able to predict basic topologies of RNA molecules with sizes up to about 50-70 nucleotides, based on their sequences only, and larger molecules if supplied with appropriate distance restraints. However, it should be noted that the current version of SimRNA, as well as other methods for RNA 3D structure prediction, exhibit a number of limitations, which reduce the accuracy of RNA 3D structure models obtained. One of the biggest challenges is the prediction of non-canonical base pairs, which are crucial for the formation of functional motifs in RNA structure. Current studies and developments are focused on a new version of SimRNA, which will overcome the key limitations that exist in the current version of the program, as well as general limitations in current methods for RNA 3D structure prediction. The major idea is to split all the contacts corresponding to base-base interactions into classes that describe specific types of base-base interactions (canonical and non-canonical), while derivation of the statistical potential.

Acknowledgments: This work was supported by the Polish National Science Center Poland (NCN) (grant 2016/23/B/ST6/03433 to M.J.B.)

[1] M.J. Boniecki, G. Lach, W.K. Dawson, K. Tomala, P. Lukasz, T. Soltysinski, K.M. Rother, J.M. Bujnicki, Nucleic Acids Res. 2016 Apr 20;44(7):e63

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