Why Can’t We Predict RNA Structure At Atomic Resolution?
No existing algorithm can start with arbitrary RNA sequences and return the precise three-dimensional structures that ensure 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.
Note added in proof
Since the time of writing (2010), we have described a method called stepwise assembly that appears to resolve the conformational sampling bottleneck for small RNA loops (Sripakdeevong et al. 2011). Further, we and others have initiated RNA-Puzzles, a series of community-wide blind trials for RNA structure prediction (Cruz et al. 2012).
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