Innovative Multi-Epitope Vaccine Development for Rheumatoid Arthritis Via Immunoinformatics Publisher Pubmed



Shadidizaji A ; Ghalamfarsa F ; Cinisli KT ; Esmailnia G ; Okkay U ; Hacimuftuoglu A ; Sagsoz ME ; Fazli Y ; Jannesar R ; Warda M ; Taskin M
Source: Human Immunology Published:2026

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disorder marked by persistent joint inflammation, pain, and progressive disability, affecting millions worldwide. Current therapies, including anti-inflammatory and immunosuppressive agents, provide symptomatic relief but fail to offer long-term disease control or immune tolerance, highlighting the need for innovative therapeutic strategies. Here, we present a novel multi-epitope vaccine designed using immunoinformatics to target key RA-associated molecules—TNF-α, IL-23R, PTPN22, PADI2, and PADI4—critical drivers of inflammation and autoimmunity. The vaccine incorporates Melittin and GP96 as adjuvants to enhance immunogenicity while minimizing toxicity. Comprehensive in silico analyses, including epitope prediction, antigenicity, allergenicity, and physicochemical profiling, were performed to ensure safety and efficacy. Molecular docking and dynamics simulations demonstrated stable interactions with Toll-like receptor 9 (TLR9), suggesting effective immune activation. Furthermore, computational cloning and codon optimization confirmed high expression potential in a bacterial vector. In silico immune simulations predicted a Th1-biased response with sustained B-cell memory, supporting the vaccine’s potential to modulate pathogenic immune responses in RA. This study provides a rational framework for a multi-targeted immunotherapeutic approach, leveraging computational methods to accelerate vaccine development. While experimental validation is necessary, these findings lay the foundation for next-generation RA vaccines capable of disrupting autoimmune cascades at multiple levels, offering a promising path toward durable disease management. © 2026 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.