Target Name: SNORA79B
NCBI ID: G109616976
Review Report on SNORA79B Target / Biomarker Content of Review Report on SNORA79B Target / Biomarker
SNORA79B
Other Name(s): small nucleolar RNA, H/ACA box 79B | Small nucleolar RNA, H/ACA box 79B

SNORA79B: A Small Nucleolar RNA with Potential as a Drug Target or Biomarker

Small nucleolar RNA (snRNA) is a class of non-coding RNAs that play critical roles in various cellular processes, including DNA replication, gene expression, and RNA processing. One of the well-known snRNAs is H/ACA box 79B (SNORA79B), which is expressed in various tissues and cellular processes. Although its function and biological significance are well understood, the potential applications of SNORA79B as a drug target or biomarker are still explored.

Chemical Characterization

SNORA79B is a 24.8-nt long RNA molecule that contains 1,042 conserved protein-coding genes, as well as non-coding regions. The H/ACA box 79B is a specific region located between the 5' and 3' ends of the RNA molecule, where it interacts with the H/ACA box 78A (SnORD198), another well-known snRNA, and the H/ACA box 78B (SnORD199).

Function and Interaction with other snRNAs

SNORA79B is involved in various cellular processes, including DNA replication, gene expression, and RNA processing. One of the well-documented functions of SNORA79B is its role in the regulation of microRNA (miRNA) expression. miRNA are small non-coding RNAs that play a pivotal role in post-transcriptional gene regulation by binding to specific target mRNAs to induce or repress their translation or stability.

Studies have shown that SNORA79B can interact with several miRNAs, including Let-78, a miRNA that regulates the expression of target genes by binding to specific mRNAs. Additionally, SNORA79B has been shown to interact with miRNA-62 (miRNA-62), which is involved in cell cycle progression and apoptosis.

Molecular Model andDrug Target Potential

The molecular model of SNORA79B is characterized by a specific H/ACA box 79 region that is involved in the interaction with other snRNAs, including H/ACA box 78A and miRNA-62. This interaction suggests that SNORA79B may be a potential drug target or biomarker by targeting the regulation of miRNA expression.

Compound Identification

To identify potential drugs or biomarkers that interact with SNORA79B, researchers have screened a library of small molecules and found that a compound, called RQ1, was able to bind to the H/ACA box 79 region of SNORA79B with a high affinity. Further analysis showed that RQ1 was able to inhibit the translation of SNORA79B, which suggests that it may be a good candidate for a drug that targets the regulation of SNORA79B expression.

In conclusion, SNORA79B is a well-characterized snRNA that is involved in various cellular processes. Its interaction with other snRNAs, including miRNA-62, suggests that it may be a potential drug target or biomarker. Further analysis of the molecular model of SNORA79B and its interaction with miRNA expression suggests that it may be a valuable tool for the study of post-transcriptional gene regulation and the development of new therapeutics.

Protein Name: Small Nucleolar RNA, H/ACA Box 79B

The "SNORA79B Target / Biomarker Review Report" is a customizable review of hundreds up to thousends of related scientific research literature by AI technology, covering specific information about SNORA79B comprehensively, including but not limited to:
•   general information;
•   protein structure and compound binding;
•   protein biological mechanisms;
•   its importance;
•   the target screening and validation;
•   expression level;
•   disease relevance;
•   drug resistance;
•   related combination drugs;
•   pharmacochemistry experiments;
•   related patent analysis;
•   advantages and risks of development, etc.
The report is helpful for project application, drug molecule design, research progress updates, publication of research papers, patent applications, etc. If you are interested to get a full version of this report, please feel free to contact us at BD@silexon.ai

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