The RNA secondary structure is mainly consist of a stem structure formed by complementary pairing of contiguous bases and a cyclic structure formed by non-pairing of bases. This RNA secondary structure is also called the stem-and-loop structure, As long as all the paired bases of an RNA sequence are determined, the secondary structure of the entire RNA can be determined.
There are 16 possible base-pairings, however of these, only six (AU, GU, GC, UA, UG, CG) are stable enough to form actual base-pairs. The rest are called mismatches and occur at very low frequencies in helices. RNA molecules, such as ribosomal RNAs and transfer RNAs, have an important role. Their structure cannot easily be disrupted without impact on their function and lethal consequences and selection is acting to maintain the secondary structure.
The nature of the bases is not important and substitutions are possible as long as they preserve the secondary structure. One can model the evolution of stems using the DNA models but there may be a substantial bias in results because paired substitutions would seem far less probable than they are in reality. Statistics become invalid and it can have an effect on inferred phylogenies.
A more efficient algorithm for RNA secondary structure prediction is the CDPfold that combines a convolutional neural network and dynamic programming as well as a sequence alignment method.
The second category of mainstream RNA secondary structure prediction algorithms refers to the comparative sequence analysis methods. In biological experiments, it is usually necessary to simultaneously process one or more sets of homologous RNA sequences. It is generally believed that in homologous RNA molecules, the conservation of the structure is greater than the conservation of the sequence. For example, the secondary structures of all tRNA molecules are clover-shaped. This consistency of shape gives tRNA molecules the structural consistency they need to perform similar functions. Therefore, the comparing sequence method can improve prediction accuracy to a certain extent.
RNA transcripts fold into secondary structures via intricate patterns of base pairing. These secondary structures impart catalytic, ligand binding, and scaffolding functions to a wide array of RNAs, forming a critical node of biological regulation. Among their many functions, RNA structural elements modulate epigenetic marks, alter mRNA stability and translation, regulate alternative splicing, transduce signals, and scaffold large macromolecular complexes. Thus, the study of RNA secondary structure is vital to understand the function and regulation of RNA transcripts.