Abstract

IN SILICO ANALYSIS AND MOLECULAR DOCKING TO PREDICT THE IMPACT OF GENES ASSOCIATED WITH RHEUMATOID ARTHRITIS

Krishna Kumar Das, Himansu Sekhar Behera and Santosh Kumar Behera*

Abstract

Autoimmune diseases (ADs) are often intractable because their cause are unknown and is defined as "a clinical syndrome caused by the activation of T cells or B cells, or both, in the absence of an ongoing infection or other discernible cause". However, the genetic background of patients is generally believed to be important. ADs include diabetes, rheumatoid arthritis, Graves' disease, systemic lupus and inflammatory bowel disease (IBD). The present investigation was carried out to explore the genes and their interactions pertaining to Rheumatoid arthritis (RA) which is through In-silico and molecular docking analysis. In the present study the functional annotation of a total of 267 genes from GWAS was performed through Gene Ontology (GO) analysis using DAVID which reported 216 genes and 238 GO terms for biological processes (BP). The STRING database reported the genes namely STAT4, CD40, CD28, CD247, HLA-DRB1, IRF8, IRF4, REL, EOMES, CSF2, IL2, IL3, TYK2, CSF2 and CD5 at the core region of the RA network of 216 BP genes. The Drug association analysis of WebGestalt has reported 28 drugs interacted with 41 genes or its corresponding proteins out of which docking was performed for 15drugs and 18 potential targets as they are found to be key regulators in RA disease. The molecular docking studies have reported the 24 ligand-protein interactions. Seeking the importance of genetic background of RA patients further studies can be done by mining of non-synonymous SNPs associated with genes for causing RA.

Keywords: Rheumatoid Arthritis; autoimmune diseases; Gene Ontology; biological processes; Inflammatory Bowel Disease.