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RNA Structure01:23

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The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
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The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
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Ribosomal RNA (rRNA) sequence analysis revealed three distinct groups of cells: eukaryotes, bacteria, and archaea. In 1978, Carl R. Woese proposed the concept of domains, a taxonomic level above kingdoms, to differentiate these groups. He suggested that archaea and bacteria, despite their similar appearance, represent separate domains. Domains differ in rRNA, membrane lipid structure, transfer RNA, and antibiotic sensitivity.In this classification, animals, plants, and fungi belong to the...
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RR3DD: an RNA global structure-based RNA three-dimensional structural classification database.

Xu Hong1, Jinfang Zheng1, Juan Xie1

  • 1School of Physics, Huazhong University of Science and Technology, Wuhan, China.

RNA Biology
|October 19, 2021
PubMed
Summary
This summary is machine-generated.

A new RNA 3D structure database, RR3DD, classifies RNA folds using global structural similarity. This resource aids in RNA structure prediction and function annotation, improving upon outdated databases.

Keywords:
RNA classificationRNA structuredatabasestructure alignment

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Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • RNA 3D structure is crucial for RNA-binding protein recognition.
  • Existing RNA databases like SCOR and DARTS, based on sequence and structure, are outdated.
  • Accurate RNA classification is vital for structure prediction and function annotation.

Purpose of the Study:

  • To develop a novel RNA classification database, RR3DD, based on global 3D structural similarity.
  • To provide an updated and comprehensive resource for studying RNA structure and function.
  • To offer tools for RNA structure annotation and homology modeling.

Main Methods:

  • Collected 13,601 RNA chains from PDB and mmCIF formats.
  • Classified RNA chains into 780 RNA folds using global 3D structural similarity.
  • Aligned and clustered RNA chains from PDB and mmCIF into 675 and 220 RNA folds, respectively.
  • Developed a web interface for browsing, annotation, and template searching.

Main Results:

  • RR3DD database established with 780 RNA folds.
  • Identified 11 clusters with over 50 members, including rRNAs, riboswitches, and tRNAs.
  • Demonstrated successful annotation of previously unclassified RNAs by mapping RR3DD to Rfam.
  • Showcased accurate grouping of tRNAs within RR3DD, distinct from Rfam classification.

Conclusions:

  • RR3DD provides a valuable, up-to-date resource for RNA structural classification.
  • The database enhances RNA structure prediction and function annotation capabilities.
  • RR3DD facilitates improved understanding of RNA families and structural relationships.