RESUMO
Interaction of nucleic acid molecules is essential for their functional roles in the cell and their applications in biotechnology. While simple duplex interactions have been studied before, the problem of efficiently predicting the minimum free energy structure of more complex interactions with possibly pseudoknotted structures remains a challenge. In this work, we introduce a novel and efficient algorithm for prediction of Duplex Interaction of Nucleic acids with pseudoKnots, DinoKnot follows the hierarchical folding hypothesis to predict the secondary structure of two interacting nucleic acid strands (both homo- and hetero-dimers). DinoKnot utilizes the structure of molecules before interaction as a guide to find their duplex structure allowing for possible base pair competitions. To showcase DinoKnots's capabilities we evaluated its predicted structures against (1) experimental results for SARS-CoV-2 genome and nine primer-probe sets, (2) a clinically verified example of a mutation affecting detection, and (3) a known nucleic acid interaction involving a pseudoknot. In addition, we compared our results against our closest competition, RNAcofold, further highlighting DinoKnot's strengths. We believe DinoKnot can be utilized for various applications including screening new variants for potential detection issues and supporting existing applications involving DNA/RNA interactions, adding structural considerations to the interaction to elicit functional information.