  We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained
representation of RNA designed for structure prediction and refinement. In our
approach, the representation of a nucleotide consists of a point particle for
the phosphate group and an anisotropic particle for the nucleoside. The
interactions are, in principle, knowledge-based potentials inspired by the
ESCORE function, a base-centered scoring function. However, a special treatment
is given to base-pairing interactions and certain geometrical conformations
which are lost in a raw knowledge-base model. This results in a representation
able to describe planar canonical and non-canonical base pairs and
base-phosphate interactions and to distinguish sugar puckers and glycosidic
torsion conformations. The model is applied to the folding of several
structures, including duplexes with internal loops of non-canonical base pairs,
tetraloops, junctions and a pseudoknot. For the majority of these systems,
experimental structures are correctly predicted at the level of individual
contacts. We also propose a method for efficiently reintroducing atomistic
detail from the coarse-grained representation.
