Predicting Rheumatoid Arthritis Associated Significant Amino-Acid Residues Using Residue-Residue Interaction Analysis

Abstract

Rheumatoid Arthritis (RA) is a prevalent autoimmune and inflammatory disease that requires restructuring. A lot of research information is available, but a clear etiology and drug target information is still unclear. A bottom-up approach can add more information to existing knowledge about RA. One better way of understanding the disease-related mechanism and drug objectives can be a detailed residue-residue interaction of the proteins involved with RA. In the current research work, we have studied the significant proteins reported in the Indian population that are involved in RA progression and have represented each of them as a complex network of amino acid residues to understand the significance of individual residues in the network. We implied the graph theory approach to identity central important residue, based on topological properties of the network. This approach allows us to look at a more precise method to identify potential drug targets. Our result identified leucine, phenylalanine, tyrosine, and tryptophan as essential nodes in the network, their activity was mainly connected with immune system. Understanding the function of these amino acids in CTLA4, CD40, IRF5, IL2RB, and TRAF could lead to a new treatment options in the fight against Rheumatoid Arthritis. Bangladesh Journal of Medical Science Vol. 21 No. 04 October’22 Page : 698-710