  No existing algorithm can start with arbitrary RNA sequences and return the
precise, three-dimensional structures that ensures their biological function.
This chapter outlines current algorithms for automated RNA structure prediction
(including our own FARNA-FARFAR), highlights their successes, and dissects
their limitations, using a tetraloop and the sarcin/ricin motif as examples.
The barriers to future advances are considered in light of three particular
challenges: improving computational sampling, reducing reliance on
experimentally solved structures, and avoiding coarse-grained representations
of atomic-level interactions. To help meet these challenges and better
understand the current state of the field, we propose an ongoing community-wide
CASP-style experiment for evaluating the performance of current structure
prediction algorithms.
