miRVim: Three-dimensional miRNA Structure Database.

Vishal Kumar Sahu, Ankita Subhadarsani Parida, Amit Ranjan, Harishkumar Madhyastha, Soumya Basu
{"title":"miRVim: Three-dimensional miRNA Structure Database.","authors":"Vishal Kumar Sahu, Ankita Subhadarsani Parida, Amit Ranjan, Harishkumar Madhyastha, Soumya Basu","doi":"10.2174/0122115366307988240809045125","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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 Homo sapiens manifest miRNA expression.</p><p><strong>Method: </strong>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, the 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.</p><p><strong>Results: </strong>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. 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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":38067,"journal":{"name":"MicroRNA (Shariqah, United Arab Emirates)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MicroRNA (Shariqah, United Arab Emirates)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/0122115366307988240809045125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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 Homo sapiens manifest miRNA expression.

Method: 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, the 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.

Results: 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. 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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
miRVim:三维 miRNA 结构数据库。
引言微RNA(miRNA)是一类独特的非编码RNA,在包括人类、动物和植物在内的多种生物体中发挥着多方面的调控功能。在所有物种中,已发现的 miRNA 约有 60,000 个,而在智人中,有 1,926 个表现为 miRNA 表达:方法:过去几十年来,研究人员一直在探索 miRNA 的治疗作用,随着我们对 RNA 靶向认识的不断深入,miRNA 已成为重要的治疗靶点。然而,由于通过实验确定的 miRNA 结构有限,依赖虚拟筛选或计算方法(包括机器学习和人工智能)的药物发现工作受到限制:为了弥补这一空白,我们开发了 miRVim,它提供了一个人类 miRNA 结构库,这些结构来自二维(MXFold2、CentroidFold 和 RNAFold)和三维(RNAComposer 和 3dRNA)结构预测算法,此外还有来自 RCSB PDB 库的实验可用结构。该数据库旨在促进药物发现的计算数据分析,为 RNA 生物学领域基于机器学习的预测等先进技术开辟新的途径:可在 https://mirna.in/miRVim 上公开访问的 miRVim 提供的结构为研究界提供了宝贵的资源,推动了 miRNA 相关计算分析和药物发现领域的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
30
期刊最新文献
The Role of Noncoding RNAs in the Prognosis and Diagnosis of Colorectal Cancer: An Emerging Biomarker. Nanoparticle Carriers: A New Era of Precise CRISPR/Cas9 Gene Editing. Identification of Key miRNAs in Endometriosis. Key LncRNAs Associated with Distant Metastasis in Breast Cancer: A System Biology Analysis. Identification of miR-20a as a Diagnostic and Prognostic Biomarker in Colorectal Cancer: MicroRNA Sequencing and Machine Learning Analysis.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1