Literature DB >> 30325405

MicroRNA-small molecule association identification: from experimental results to computational models.

Xing Chen1, Na-Na Guan2, Ya-Zhou Sun2, Jian-Qiang Li2, Jia Qu1.   

Abstract

Small molecule is a kind of low molecular weight organic compound with variety of biological functions. Studies have indicated that small molecules can inhibit a specific function of a multifunctional protein or disrupt protein-protein interactions and may have beneficial or detrimental effect against diseases. MicroRNAs (miRNAs) play crucial roles in cellular biology, which makes it possible to develop miRNA as diagnostics and therapeutic targets. Several drug-like compound libraries were screened successfully against different miRNAs in cellular assays further demonstrating the possibility of targeting miRNAs with small molecules. In this review, we summarized the concept and functions of small molecule and miRNAs. Especially, five aspects of miRNA functions were exhibited in detail with individual examples. In addition, four disease states that have been linked to miRNA alterations were summed up. Then, small molecules related to four important miRNAs miR-21, 122, 4644 and 27 were selected for introduction. Some important publicly accessible databases and web servers of the experimentally validated or potential small molecule-miRNA associations were discussed. Identifying small molecule targeting miRNAs has become an important goal of biomedical research. Thus, several experimental and computational models have been developed and implemented to identify novel small molecule-miRNA associations. Here, we reviewed four experimental techniques used in the past few years to search for small-molecule inhibitors of miRNAs, as well as three types of models of predicting small molecule-miRNA associations from different perspectives. Finally, we summarized the limitations of existing methods and discussed the future directions for further development of computational models.

Entities:  

Year:  2018        PMID: 30325405     DOI: 10.1093/bib/bby098

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  26 in total

1.  SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association.

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Journal:  RNA Biol       Date:  2019-11-27       Impact factor: 4.652

2.  ncRPheno: a comprehensive database platform for identification and validation of disease related noncoding RNAs.

Authors:  Wenliang Zhang; Guocai Yao; Jianbo Wang; Minglei Yang; Jing Wang; Haiyue Zhang; Weizhong Li
Journal:  RNA Biol       Date:  2020-03-26       Impact factor: 4.652

Review 3.  Circular RNAs and complex diseases: from experimental results to computational models.

Authors:  Chun-Chun Wang; Chen-Di Han; Qi Zhao; Xing Chen
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

4.  Identification and Analysis of Human Microbe-Disease Associations by Matrix Decomposition and Label Propagation.

Authors:  Jia Qu; Yan Zhao; Jun Yin
Journal:  Front Microbiol       Date:  2019-02-26       Impact factor: 5.640

5.  Discovering Links Between Side Effects and Drugs Using a Diffusion Based Method.

Authors:  Mohan Timilsina; Meera Tandan; Mathieu d'Aquin; Haixuan Yang
Journal:  Sci Rep       Date:  2019-07-18       Impact factor: 4.379

6.  Insights about multi-targeting and synergistic neuromodulators in Ayurvedic herbs against epilepsy: integrated computational studies on drug-target and protein-protein interaction networks.

Authors:  Neha Choudhary; Vikram Singh
Journal:  Sci Rep       Date:  2019-07-22       Impact factor: 4.379

Review 7.  Machine and deep learning approaches for cancer drug repurposing.

Authors:  Naiem T Issa; Vasileios Stathias; Stephan Schürer; Sivanesan Dakshanamurthy
Journal:  Semin Cancer Biol       Date:  2020-01-03       Impact factor: 15.707

8.  Identification of Cancer Hallmarks Based on the Gene Co-expression Networks of Seven Cancers.

Authors:  Ling-Hao Yu; Qin-Wei Huang; Xiong-Hui Zhou
Journal:  Front Genet       Date:  2019-02-19       Impact factor: 4.599

9.  LPI-IBNRA: Long Non-coding RNA-Protein Interaction Prediction Based on Improved Bipartite Network Recommender Algorithm.

Authors:  Guobo Xie; Cuiming Wu; Yuping Sun; Zhiliang Fan; Jianghui Liu
Journal:  Front Genet       Date:  2019-04-18       Impact factor: 4.599

Review 10.  Noncoding RNA therapeutics - challenges and potential solutions.

Authors:  Melanie Winkle; Sherien M El-Daly; Muller Fabbri; George A Calin
Journal:  Nat Rev Drug Discov       Date:  2021-06-18       Impact factor: 84.694

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