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Analysis of Junctions in RNA with Coaxial Stacked Helices
Author(s) -
Fuhr Katherine Niccole,
Laing Christian,
Kim Namhee,
Schlick Tamar
Publication year - 2012
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.26.1_supplement.948.1
Subject(s) - rna , coaxial , base pair , midpoint , crystallography , nucleotide , euclidean distance , chemistry , physics , molecular physics , mathematics , geometry , computer science , gene , biochemistry , telecommunications
The structure of RNA is hierarchical and complex. The secondary and tertiary structure is related to the function of RNA. In order to help predict the structure of RNA, analysis of motifs (commonly occurring interactions and sequences) must be done. In coaxial stacked helices of 3–10 way junctions, we measured the length (number of nucleotides) of the single strand, Ji/(i+1), which connects the two helices, and predicted that as the length of the single strand increases, that the distance between the midpoints of the terminal base pairs of the helices will also increase. Using the C1’ atom of each terminal base pair, we measure the respective midpoints and calculate the overall Euclidean distance. Use of Protein Data Bank data allowed us to gather the Cartesian coordinates of the atoms for use in our calculations. We analyzed junctions with degrees 3–10. We found that 3 and 4‐way junctions are highly correlated to the length of the single strand. We also found that frequency of coaxial stacks in junctions do not signify that there will be high correlation in a linear relationship. Outliers in the data often were involved in other interactions, such as RNA‐RNA complexes, RNA‐ligand complexes, and other factors such as unusual conformations. Further analysis of 3 and 4‐way junctions according to their respective family type gave us the normal distributions of lengths and how they correspond to the previously set parameters of the family. The distributions can act as a guide in synthesis for creating certain motifs in RNA. These results can be used in prediction software of RNA and can be further investigated as more RNA is discovered.