RNA (Ribonucleic acid) Motifs are tertiary structures that play an important role in the folding mechanism of the RNA molecule. The overall function of a RNA Motif depends on its specific bp (base pairs) sequence that constitutes the secondary structure. Data mining is a novel method in both discovering potential tertiary structures within DNA (Deoxyribonucleic acid), RNA, and protein molecules and storing the information in databases. The RNA Motif of interest is the tetraloop-tetraloop receptor, which is composed of a highly conserved 11 nt (nucleotide) sequence and a tetraloop with the generic form of GNRA (where N = any base and R = A or U). There consists of eight variations of the tetraloop in the tertiary structure of the RNA motif.

The initial procedure in data mining the tetraloop-tetraloop receptor is to search for all potential PDB (Protein Data Bank) files that contain the particular RNA Motif. Once all the PDB files have been allocated, each individual file will need to be processed by RNAView to convert them to Xml format. Xml files are excellent in that they give a great in-depth summary of the residue bp and position within the molecule. Parsing each Xml file by a custom written, advanced python script will give a text file output pertaining to in which PDB files may or may not contain the full tertiary structure of the tetraloop-tetraloop receptor. The results lead to the GAAA tetraloop as well as the highly conserved 11 nt sequence which together form a tertiary structure, residing in nine PDB files.