Bioinformatics Analysis of Molecular Mimicry Between Human Microbiome Antigens and Autoimmune Receptors in Multiple Sclerosis

Abstract

Multiple Sclerosis (MS) is a chronic autoimmune disease characterized by neuroinflammation and demyelination of the central nervous system. While genetic predispositions like the HLA-DRB1*15:01 allele are well-documented, environmental triggers—particularly gut and oral dysbiosis—are increasingly implied in initiating the aberrant immune response. Molecular mimicry, where microbial antigens share structural or sequence homology with self-antigens, is a primary mechanism hypothesized to drive this autoreactivity. This study aims to systematically screen, model, and evaluate potential molecular mimicry between the human microbiome proteome and key MS-associated neuro-autoantigens (Myelin Basic Protein [MBP], Proteolipid Protein [PLP], and Myelin Oligodendrocyte Glycoprotein [MOG]) at both sequence and 3D structural levels. An integrated in silico pipeline was developed. High-throughput sequence alignment was performed using BLASTp (optimized for short, exact matches) to cross-reference MS autoantigens against a curated database of MS-associated microbial proteomes (e.g., Akkermansia muciniphila, Bacteroides fragilis). Epitopes were filtered using the Immune Epitope Database (IEDB) to predict binding affinity to the HLA-DRB1*15:01 restriction element. Candidates with an IC50 < 500 nM were modeled in 3D using AlphaFold3/ESMFold. Structural mimicry was quantified via backbone superimposition (TM-align/PyMOL), filtering for a Root-Mean-Square Deviation (RMSD) < 2.0 Å. Finally, molecular docking simulations via AutoDock Vina/HADDOCK evaluated peptide-MHC binding kinetics and subsequent T-cell  receptor (TCR) cross-activation. We expect to identify a distinct repertoire of gut and oral microbial peptides exhibiting high sequence and conformational homology to myelin epitopes. Top candidates are predicted to display robust stable binding energies within the HLA-DRB1*15:01 cleft and effectively engage MS-specific TCRs, demonstrating functional cross-reactivity. This computational framework provides a high-resolution map of microbial triggers in MS, highlighting specific therapeutic targets for microbiome-derived interventions and offering deeper insights into the environmental etiology of autoimmune demyelination.