25th International Congress on Pharmaceutical Biotechnology
Shahid Beheshti University of Medical sciences, Tehran, Iran
Title: Adalimumab Antibody Affinity Maturation: an In Silico Approach
Biography: Shirin Eyvazi
Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease that occurs in about 5 per 1000 people. Tumor necrosis factor-α (TNF-α) is an inflammatory marker in the inflammatory processes of RA. Therefore, TNF-α might serve as a therapeutic target for the treatment of RA. Adalimumab is a human monoclonal antibody (IgG1) against TNF-α which has been approved by FDA for the treatment of arthritis and other inflammatory related diseases. For a successful immunotherapy the different features of therapeutic antibodies such as binding affinity should be improved. In this regard, we have lunched an in silico approach to increase the affinity of adalimumab to TNF-α. We find the important amino acids of the adalimumab antibody using different software and web servers, and then replaced these amino acids with others to improve antibody binding affinity. Finally, we examined the binding affinity of antibody variants to the antigen using different docking programs. The results indicated that the replaced new amino acids in the binding site of adalimumab increase the affinity of the antibody to TNF-α. In conclusion it should be pointed out that, the employed in silico approach could pave the way for increasing the affinity of antibodies. Increased affinity enhances the biological action of the antibody, which in turn improves the therapeutic effects. Furthermore, the increased antibody affinity can reduce the therapeutic dose of the antibody, resulting in lower toxicity and handling cost.