  RNA structure prediction is a challenging problem, especially with
pseudoknots. Recently, there has been a shift from the classical minimum free
energy-based methods (MFE) to partition function-based ones that assemble
structures using base-pairing probabilities. Two examples of the latter group
are the popular maximum expected accuracy (MEA) method and the ProbKnot method.
ProbKnot is a fast heuristic that pairs nucleotides that are reciprocally most
probable pairing partners, and unlike MEA, can also predict structures with
pseudoknots. However, ProbKnot's full potential has been largely overlooked. In
particular, when introduced, it did not have an MEA-like hyperparameter that
can balance between positive predictive value (PPV) and sensitivity. We show
that a simple thresholded version of ProbKnot, which we call ThreshKnot, leads
to more accurate overall predictions by filtering out unlikely pairs whose
probabilities fall under a given threshold. We also show that on three
widely-used folding engines (RNAstructure, Vienna RNAfold, and CONTRAfold),
ThreshKnot always outperforms the much more involved MEA algorithm in (1) its
higher structure prediction accuracy, (2) its capability to predict
pseudoknots, and (3) its faster runtime and easier implementation. This
suggests that ThreshKnot should replace MEA as the default partition
function-based structure prediction algorithm. ThreshKnot is already available
in the widely used RNAstructure software package version 6.2 (released November
27, 2019): https://rna.urmc.rochester.edu/RNAstructure.html
