Table 11.

Advantages and shortcomings of MFE-based RIP and RSP tools

Type of RIP and RSP Tools	Advantages	Shortcomings	Ref.
Nussinov algorithm	The first DDP algorithm Efficient prediction of RNA molecule's optimal folding state through maximum base pairings calculation Show pattern of primary RNA structure Similar algorithmic structure as Zuker (energy minimization) Prediction of (restricted) crossing structure can be seen as an extension	No stacking of base-pairing considered Loop sizes not distinguished No special scoring of multiloops Inability to predict pseudoknotted helices Prediction of only one structure Not applicable to secondary RNA structures No suboptimal solutions Destabilization of multibranch loops/helical junctions Discontinuity in the formed base-pairs Low prediction accuracy High false positive base-pairs prediction	[114, 119–123, 285]
Interaction-only	Fast algorithmic speed Incorporating conservation data enhances specificity, leading to improved overall MCC performance A detailed view of RRIs	Lower accuracy Only consider intermolecular base-pairs during computation and in the final predicted outcome Heavy reliance on the energies of stacked back-to-back base-pairs, interior loops, and bulges for RIP Long interior loops are limited or excluded	[87, 127, 142, 203]
Accessibility-based	Prediction of both intra- and intermolecular base-pairs Suitable for all types of RRIs Compatible with eukaryotic and bacterial datasets Computation of RNA accessibility Prediction of multiple binding sites Ability to differentiate native interactions from a background in the bacterial dataset Ideal for de novo predictions, especially those with smaller run-times such as IntaRNA and RNAplex	Inclusion of MSA might decrease performance due to alignments of questionable quality The number of variables (such as alignment, percent of identity threshold, and suboptimal results settings) make it impractical in a de novo setting	[86, 138, 139]
Concatenation-based	Prediction of both intra- and intermolecular base-pairs Prediction of RNA secondary structures of single-stranded RNA sequences upon dimer formation Capable of handling multiple RNA strands	Challenge in predicting accurate pseudoknots Often computationally demanding, especially for large RNA molecules	[87, 143]

MCC: Matthews correlation coefficient; MSA: multiple sequence alignment; RIP: RNA–RNA interaction prediction; RNA: ribonucleic acid; RRI: RNA–RNA interaction; RSP: RNA structure prediction