Computational approaches in exploring the role of microRNAs in Human Cytomegalovirus infection

Abstract

Computational methods play a significant role in understanding the interaction between HCMV-encoded miRNAs with their targets. MicroRNAs have a regulatory role in post-transcriptional gene expression thereby resulting in translational repression or mRNA degradation. The Human Cytomegalovirus, a Herpesviridae family encodes their own collection of miRNAs which help to modulate the viral and host gene expression and facilitate the viral replication and immune evasion. Precise HCMV-encoded miRNA target prediction has a pivotal role in unrevealing the complex regulatory network in virus -host interaction. Nowadays, computational approaches have become increasingly important in identifying novel miRNAs and their target genes because of the traditionally methods which relied on experimental techniques are time consuming and often costly. In this review computational methods and key criteria important in the HCMV-encoded miRNA target prediction like sequence complementarity, thermodynamic stability, evolutionary conservation and advanced machine learning based techniques have been discussed.