Fitness functions for RNA structure design

Abstract

An RNA design algorithm takes a target RNA structure and finds a sequence that folds into that structure. This is fundamentally important for engineering therapeutics using RNA. Computational RNA design algorithms are guided by fitness functions, but not much research has been done on the merits of these functions. We survey current RNA design approaches with a particular focus on the fitness functions used. We experimentally compare the most widely used fitness functions in RNA design algorithms on both synthetic and natural sequences. It has been almost 20 years since the last comparison was published, and we find similar results with a major new result: maximizing probability outperforms minimizing ensemble defect. The probability is the likelihood of a structure at equilibrium and the ensemble defect is the weighted average number of incorrect positions in the ensemble. We find that maximizing probability leads to better results on synthetic RNA design puzzles and agrees more often than other fitness functions with natural sequences and structures, which were designed by evolution. Also, we observe that many recently published approaches minimize structure distance to the minimum free energy prediction, which we find to be a poor fitness function.

Figure 1.

Comparison between probability, ensemble defect, and structure distance on real RNA sequences with known structures. Shows the cumulative number of RNAs for which the true structure (or the closest analog) was at or under a certain percentile when ranked by a fitness function against other structures.

Figure 2.

A sample of the structures for a tRNA (Saccharomyces cerevisiae tdbR00000083). Colors correspond to nucleotides in the true structure depicted on the left. The top row is ranked by probability and the bottom row is ranked by ensemble defect.

Figure 3.

A sample of the structures for a small SRP (Deinococcus radiodurans Dein.radi._AE000513). Colors correspond to nucleotides in the true structure depicted on the left. The top row is ranked by probability and the bottom row is ranked by ensemble defect.