IN SILICO MODELING OF THE MOLECULAR STRUCTURE OF microRNAs MARKERS FOR LIVER FIBROSIS IN HEPATITIS C

Abstract

Molecular biology looks for evidence that microRNA (miRNAs) plays a relevant function both in the beginning and advanced stages of hepatic fibrosis (HF), and has been proposed as an additional biomarker for HF forecasting in carriers of hepatitis C virus (HCV) infection. The purpose of this study was to develop an in silico modeling of the two-dimensional (2D) molecular structure of miRNA markers for HF in carriers of HCV. A search was initially performed for the nucleotide sequence of 6 miRNAs defined as biomarkers for HF, performinga computational simulation of the molecular structure of the following miRNAs: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The nucleotide sequences were chosen in the GenBank of the American National Institutes of Health genetic sequence database. The nucleotide sequence alignment was carried out with a text-based format (FASTA) tool. In the molecular modeling, the structures were built with the RNAstructure, a completely automated miRNAs structure modelling server, available through Web Servers for RNA Secondary Structure Prediction. This study presented the nucleotide sequence and the computational simulation of molecular structures for the following miRNA: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The molecular structure of miRNAs markers for HF in HCV carriers, through computational biology, is essential for designing more efficient optional tools for accurate treatment. 
 KEY WORDS: micro-RNA; Hepatitis C; Hepatic Fibrosis; Computational Biology.