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Contemporary Oncology
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A computational approach to the study of interactions between proteins and miR10-b, miR-335, and miR-21 involved in breast cancer

Authors: Rahma Hammou; Yassine Kasmi; Moulay Ennaji;

A computational approach to the study of interactions between proteins and miR10-b, miR-335, and miR-21 involved in breast cancer

Abstract

MiR-10b, miR-335, and miR-21 are classes of microRNAs (miRNAs) that are overexpressed in breast cancer. Thus, in our study we aimed to test the hypothesis that miRNAs may have direct interactions with proteins and the possibility to inhibit/activate the functional site of proteins and enzymes. For this purpose, we choose three miRNAs involved in breast cancer to study interactions between some proteins and genes, including BRCA1 and PTEN, by processing the docking and matching tools using the Hex8 and HADDOCK server. Mathematically, the hidden Markov models were created by using MATLAB script according to the algorithm in order to study and validate the interactions and bonds between proteins and miRNAs. The main results demonstrate the ability of miR-10b, miR-335, and miR-21 to create direct interactions with 3D protein structures. Furthermore, these results may lead to another pathway of research, i.e. the direct interaction between proteins and their sub-units, to highlight the data obtained previously and demonstrate that proteins may directly interact with ncRNA instead of mRNA. Moreover, our study suggests developing research on different pathways of association proteins-miRNAs as a part of epigenetic extra-nuclear regulation. Taken together, our study provides the first evidence of direct interactions between miRNAs and proteins.

Keywords

Original Paper, mir-10b, Immunology, R, Cancer research, mir-21, gene interactions, Breast cancer, breast cancer, Oncology, Radiology Nuclear Medicine and imaging, mir-335, Medicine

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
gold
Related to Research communities
Cancer Research