RNAplex is a fast algorithm for predicting RNA-RNA interactions, developed as part of the ViennaRNA Package. Unlike tools that compute full thermodynamic models of both inter- and intramolecular structures, RNAplex uses a simplified energy model that considers only intermolecular base pairs. This makes it 10-27 times faster than comparable tools like RNAhybrid while maintaining competitive accuracy.
The tool excels at scanning long target RNAs for potential binding sites of shorter query sequences. This asymmetric search pattern makes RNAplex particularly useful for microRNA target prediction, bacterial small RNA (sRNA) target identification, and antisense oligonucleotide design.
When combined with precomputed accessibility profiles from RNAplfold, RNAplex achieves prediction accuracy comparable to the more computationally intensive RNAup while running three orders of magnitude faster.
RNAplex decomposes predicted RNA duplexes into three structural elements: stacking pairs, bulge loops, and interior loops. The algorithm uses dynamic programming with four tables representing substructures ending in base pairs, interior loops, or bulges on either sequence.
The simplified energy model ignores intramolecular structure within each RNA, focusing solely on the hybrid duplex. This approximation slightly overestimates loop energies but dramatically reduces computational complexity from O(N⁴) to O(N²), where N is sequence length.
Bulge loop penalties match the Turner thermodynamic model exactly for bulges up to 6 nucleotides. Larger loops use linear extrapolation.
Structured RNAs do not freely expose all nucleotides for interaction. RNAplex incorporates this by reading precomputed accessibility profiles that estimate the energetic cost of "opening" local secondary structure to permit intermolecular pairing.
The accessibility-enhanced mode:
Benchmarks show that accessibility-aware predictions (RNAplex, RNAup, IntaRNA) consistently outperform methods that ignore accessibility in both sensitivity and precision.
ProteinIQ provides cloud-based RNAplex predictions through a browser interface, eliminating the need to install the ViennaRNA Package locally.
| Input | Description |
|---|---|
RNA Sequence 1 | First RNA sequence (query). FASTA format or raw nucleotides. |
RNA Sequence 2 | Second RNA sequence (target). FASTA format or raw nucleotides. |
| Setting | Description |
|---|---|
Temperature | Folding temperature (0-100, default 37). Affects thermodynamic calculations. |
| Column | Description |
|---|---|
Interaction | The pair of sequence identifiers involved in the interaction. |
Hit # | Ranking of the interaction (1 = best). |
Structure | Dot-bracket notation showing the hybrid structure, with & separating the two strands. Paired bases shown as parentheses, unpaired as dots. |
Energy | Predicted binding free energy in kcal/mol. More negative values indicate stronger predicted binding. |
The binding energy indicates thermodynamic favorability:
| Energy (kcal/mol) | Interpretation |
|---|---|
| < -20 | Very strong interaction |
| -10 to -20 | Strong interaction |
| -5 to -10 | Moderate interaction |
| > -5 | Weak interaction, may not be biologically relevant |
These thresholds are approximate. Biological relevance depends on cellular context, RNA concentrations, and competing structures.
The ViennaRNA Package includes several tools for RNA-RNA interaction prediction, each suited to different use cases:
For typical workflows, RNAplex serves as an initial filter to identify candidates, which can then be analyzed more thoroughly with RNAup.
MicroRNAs bind target mRNAs through partial complementarity, typically requiring a "seed" match at positions 2-8 of the miRNA. RNAplex identifies thermodynamically favorable binding sites that can be filtered for seed matches.
Small regulatory RNAs in bacteria control gene expression by base-pairing with mRNA targets. These interactions often occur in 5' UTRs near ribosome binding sites. RNAplex enables rapid screening of potential sRNA-mRNA pairs.
Designing antisense therapeutics requires identifying accessible regions in target RNAs. RNAplex predictions help select oligonucleotide sequences most likely to hybridize efficiently.
Short interfering RNAs can silence unintended transcripts through partial complementarity. RNAplex screens for potential off-target binding sites across the transcriptome.
RNAplex predictions assume thermodynamic equilibrium and do not account for:
The simplified energy model trades some accuracy for speed. For high-confidence predictions of specific interactions, verify candidates using RNAup or experimental validation.
