背景:微RNA(miRNA),一类不同的非编码RNA,在各种生物体中发挥多方面的调节功能,包括人类,动物,和植物。在所有物种中,已识别的miRNA的库存约为60,000,和1,926在智人中显示miRNA表达。
方法:研究人员在过去的几十年中探索了它们的治疗作用,随着我们对RNA靶向的理解的进步,将它们定位为突出的治疗靶标。然而,实验确定的miRNA结构的有限可用性限制了依赖虚拟筛选或计算方法的药物发现工作,包括机器学习和人工智能。
结果:为了解决这个问题,已经开发了miRVim,提供从两个二维(MXFold2,CentroidFold,和RNAFold)和三维(RNAComposer和3dRNA)结构预测算法,除了来自RCSBPDB存储库的实验可用结构之外。miRVim包含13,971个预测的二级结构和17,045个预测的三维结构,填补了miRNA结构数据库不可用的空白。该数据库旨在促进药物发现的计算数据分析,为推进技术开辟新的途径,例如RNA生物学领域中基于机器学习的预测。
结论:miRVim提供的可公开访问的结构,可在https://mirna。in/miRVim,为研究界提供了宝贵的资源,推进miRNA相关计算分析和药物发现领域。
BACKGROUND: 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.
METHODS: 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.
CONCLUSIONS: 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.