De Novo Discovery Of Structural Motifs In Rna 3D Structures Through Clustering
Abstract
As functional components in three-dimensional (3D) conformation of an RNA, the RNA structural motifs provide an easy way to associate the molecular architectures with their biological mechanisms. In the past years, many computational tools have been developed to search motif instances by using the existing knowledge of well-studied families. Recently, with the rapidly increasing number of resolved RNA 3D structures, there is an urgent need to discover novel motifs with the newly presented information. In this work, we classify all the loops in non-redundant RNA 3D structures to detect plausible RNA structural motif families by using a clustering pipeline. Compared with other clustering approaches, our method has two benefits: first, the underlying alignment algorithm is tolerant to the variations in 3D structures. Second, sophisticated downstream analysis has been performed to ensure the clusters are valid and easily applied to further research. The final clustering results contain many interesting new variants of known motif families, such as GNAA tetraloop, kink-turn, sarcin-ricin and T-loop. We have also discovered potential novel functional motifs conserved in ribosomal RNA, sgRNA, SRP RNA, riboswitch and ribozyme.
Publication Date
5-1-2018
Publication Title
Nucleic Acids Research
Volume
46
Issue
9
Number of Pages
4783-4793
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1093/nar/gky139
Copyright Status
Unknown
Socpus ID
85064345832 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85064345832
STARS Citation
Ge, Ping; Islam, Shahidul; Zhong, Cuncong; and Zhang, Shaojie, "De Novo Discovery Of Structural Motifs In Rna 3D Structures Through Clustering" (2018). Scopus Export 2015-2019. 9820.
https://stars.library.ucf.edu/scopus2015/9820