ArticleNucleic acids research2012
Predicting kissing interactions in microRNA-target complex and assessment of microRNA activity.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 36 citations in OpenAlex.
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- Vfold2D-MC: A Physics-Based Hybrid Model for Predicting RNA Secondary Structure Folding.The journal of physical chemistry. B · 2021Article
- The three-way junction structure of the HIV-1 PBS-segment binds host enzyme important for viral infectivity.Nucleic acids research · 2021Article
- IsRNA1:Journal of chemical theory and computation · 2021Article
- Article
- Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability.Biophysical journal · 2020Article
- HNADOCK: a nucleic acid docking server for modeling RNA/DNA-RNA/DNA 3D complex structures.Nucleic acids research · 2019Article
- FMRP - G-quadruplex mRNA - miR-125a interactions: Implications for miR-125a mediated translation regulation of PSD-95 mRNA.PloS one · 2019Article
- Parathyroid hormone-induced down-regulation of miR-532-5p for matrix metalloproteinase-13 expression in rat osteoblasts.Journal of cellular biochemistry · 2018Article
- Determination of an effective scoring function for RNA-RNA interactions with a physics-based double-iterative method.Nucleic acids research · 2018Article
- CCmiR: a computational approach for competitive and cooperative microRNA binding prediction.Bioinformatics (Oxford, England) · 2018Article
- DNA-DNA kissing complexes as a new tool for the assembly of DNA nanostructures.Nucleic acids research · 2016Article
- A Method to Predict the Structure and Stability of RNA/RNA Complexes.Methods in molecular biology (Clifton, N.J.) · 2016Article
- Discovery and characterization of the first non-coding RNA that regulates gene expression, micF RNA: A historical perspective.World journal of biological chemistry · 2015Article
- Assembly and analysis of eukaryotic Argonaute-RNA complexes in microRNA-target recognition.Nucleic acids research · 2015Article
- A Method to Predict the 3D Structure of an RNA Scaffold.Methods in molecular biology (Clifton, N.J.) · 2015Article
- Many-body effect in ion binding to RNA.The Journal of chemical physics · 2014Article
- Exploring the electrostatic energy landscape for tetraloop-receptor docking.Physical chemistry chemical physics : PCCP · 2014Article
- Comprehensive annotation of microRNA expression profiles.BMC genetics · 2013Article
- Tertiary structure-based analysis of microRNA-target interactions.RNA (New York, N.Y.) · 2013Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
MicroRNAs (miRNAs) are a class of short RNA molecules that play an important role in post-transcriptional gene regulation. Computational prediction of the miRNA target sites in mRNA is crucial for understanding the mechanism of miRNA-mRNA interactions. We here develop a new computational model that allows us to treat a variety of miRNA-mRNA kissing interactions, which have been ignored in the currently existing miRNA target prediction algorithms. By including all the different inter- and intra-molecular base pairs, this new model can predict both the structural accessibility of the target sites and the binding affinity (free energy). Applications of the model to a test set of 105 miRNA-gene systems show a notably improved success rate of 83/105. We found that although the binding affinity alone predicts the miRNA repression efficiency with a high success rate of 73/105, the structure in the seed region can significantly influence the miRNA activity. The method also allows us to efficiently search for the potent miRNA from a pool of miRNA candidates for any given gene target. Furthermore, extension of the method may enable predictions of the three-dimensional (3D) structures of miRNA/mRNA complexes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.