Computational identification and molecular dynamics simulation of potential circularRNA derived peptide from gene expression profile of Rheumatoid arthritis, Alzheimer's disease, and Atrial fibrillation.
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引用次数: 0
Abstract
The two most serious global health challenges confronting human society today are autoimmune disorders (AIDs) and neurological diseases (NDs), both of which shorten people's lives and worsen the situation. Despite their extensive impact, statistics show that AIDs is associated with a higher risk of ND. Circular RNAs (circRNAs) are critical in several illnesses and disorders, especially AID and ND. Therefore, the present study focused on understanding the underlying causes of the pathophysiology of diseases such as AID and ND through in silico-based research. In order to determine how circRNAs are related to various disease pathways, this study examined the gene expression data sets for Rheumatoid arthritis (RA), Alzheimer's disease (AD), and atrial fibrillation (AF). Our study identified and analyzed two circRNAs, their respective host genes (DHTKD1 and RAN) and their related miRNAs, which could serve as potential markers for treating disorders like myotonic dystrophy type 1, spinocerebellar ataxia and fragile X syndrome. Further, the circRNA-derived peptide was identified and analysed with the molecular dynamics simulation (MDS) followed by a principal component (PC) based free energy landscape (FEL) profile. The computational results obtained here provide a basis for the development of therapeutics against AD, RA and AF. Moreover, further functional studies are needed to validate their role in disease aetiology and to provide a detailed understanding of their association with AID and ND.Communicated by Ramaswamy H. Sarma.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.