TY - JOUR
T1 - Novel features for identifying A-minors in three-dimensional RNA molecules
AU - Sheth, Palak
AU - Cervantes-Cervantes, Miguel
AU - Nagula, Akhila
AU - Laing, Christian
AU - Wang, Jason T.L.
N1 - Funding Information:
The authors thank Drs. Bruce Shapiro and Craig Zirbel for helpful conversations concerning RNA tertiary motifs and FR3D. We also thank Lei Hua, Ankur Malhotra, Alexander Nation, Meghana Vasavada and Ruchik Yajnik for their contributions in the early stage of this project. This research was supported in part by U.S. National Science Foundation under grant number IIS-0707571 .
PY - 2013
Y1 - 2013
N2 - RNA tertiary interactions or tertiary motifs are conserved structural patterns formed by pairwise interactions between nucleotides. They include base-pairing, base-stacking, and base-phosphate interactions. A-minor motifs are the most common tertiary interactions in the large ribosomal subunit. The A-minor motif is a nucleotide triple in which minor groove edges of an adenine base are inserted into the minor groove of neighboring helices, leading to interaction with a stabilizing base pair. We propose here novel features for identifying and predicting A-minor motifs in a given three-dimensional RNA molecule. By utilizing the features together with machine learning algorithms including random forests and support vector machines, we show experimentally that our approach is capable of predicting A-minor motifs in the given RNA molecule effectively, demonstrating the usefulness of the proposed approach. The techniques developed from this work will be useful for molecular biologists and biochemists to analyze RNA tertiary motifs, specifically A-minor interactions.
AB - RNA tertiary interactions or tertiary motifs are conserved structural patterns formed by pairwise interactions between nucleotides. They include base-pairing, base-stacking, and base-phosphate interactions. A-minor motifs are the most common tertiary interactions in the large ribosomal subunit. The A-minor motif is a nucleotide triple in which minor groove edges of an adenine base are inserted into the minor groove of neighboring helices, leading to interaction with a stabilizing base pair. We propose here novel features for identifying and predicting A-minor motifs in a given three-dimensional RNA molecule. By utilizing the features together with machine learning algorithms including random forests and support vector machines, we show experimentally that our approach is capable of predicting A-minor motifs in the given RNA molecule effectively, demonstrating the usefulness of the proposed approach. The techniques developed from this work will be useful for molecular biologists and biochemists to analyze RNA tertiary motifs, specifically A-minor interactions.
KW - RNA tertiary interactions
KW - Tertiary motifs
KW - Three-dimensional RNA structure
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U2 - 10.1016/j.compbiolchem.2013.10.004
DO - 10.1016/j.compbiolchem.2013.10.004
M3 - Article
C2 - 24211672
AN - SCOPUS:84887448014
SN - 1476-9271
VL - 47
SP - 240
EP - 245
JO - Computational Biology and Chemistry
JF - Computational Biology and Chemistry
ER -