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Volume 14, Issue 1
  • ISSN: 2211-5366
  • E-ISSN: 2211-5374

Abstract

Introduction

MicroRNAs (miRNAs), a distinct category of non-coding RNAs, exert multifaceted regulatory functions in a variety of organisms, including humans, animals, and plants. The inventory of identified miRNAs stands at approximately 60,000 among all species and 1,926 in manifests miRNA expression. Their theranostic role has been explored by researchers over the last few decades, positioning them as prominent therapeutic targets as our understanding of RNA targeting advances. However, limited availability of experimentally determined miRNA structures has constrained drug discovery efforts relying on virtual screening or computational methods, including machine learning and artificial intelligence.

Methods

To address this lacuna, miRVim has been developed, providing a repository of human miRNA structures derived from both two-dimensional (MXFold2, CentroidFold, and RNAFold) and three-dimensional (RNAComposer and 3dRNA) structure prediction algorithms, in addition to experimentally available structures from the RCSB PDB repository.

Results

miRVim contains 13,971 predicted secondary structures and 17,045 predicted three-dimensional structures filling the gap of unavailability of miRNA structure data bank. This database aims to facilitate computational data analysis for drug discovery, opening new avenues for advancing technologies such as machine learning-based predictions in the field of RNA biology.

Conclusion

The publicly accessible structures provided by miRVim, available at https://mirna.in/miRVim, offer a valuable resource for the research community, advancing the field of miRNA-related computational analysis and drug discovery.

© 2025 Bentham Science Publishers
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2025-05-31

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miRVim: Three-dimensional miRNA Structure Database
MicroRNA 14, 59 (2025); https://doi.org/10.2174/0122115366307988240809045125
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  • Article Type:     Research Article
Keyword(s): human miRNA structures; miRNA 3D structures; molecular modeling of miRNA; nucleic acid modelling; RNA folding; Structural bioinformatics
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