Bioinformatics analysis of myelin-microbe interactions suggests multiple types of molecular mimicry in the

Ali Bigdeli1, Mostafa Ghaderi-Zefrehei2, Bluma J Lesch3

  • 1Department of Biophysics, School of Biological Sciences, Tarbiat Modares University, Tehran, Iran.

Plos One
|January 8, 2025
PubMed

Insights

This study used bioinformatics to find viral and bacterial antigens that mimic myelin proteins, suggesting a potential trigger for multiple sclerosis (MS) and offering new therapeutic targets.

Area of Science:

  • Neuroimmunology
  • Bioinformatics
  • Infectious Disease

Background:

  • Multiple sclerosis (MS) is an autoimmune disease causing central nervous system (CNS) myelin sheath destruction.
  • Viral and bacterial infections are linked to MS onset and severity.
  • Molecular mimicry between microbial antigens and myelin components may trigger autoimmune responses.

Purpose of the Study:

  • To identify viral and bacterial antigens resembling myelin oligodendrocyte glycoprotein (MOG) and myelin basic protein (MBP) using an in-silico bioinformatics approach.
  • To investigate potential microbial triggers for MS pathogenesis.
  • To explore novel therapeutic targets for MS.

Main Methods:

  • In-silico bioinformatics analysis of protein structures and amino acid sequences.
  • Comparison of viral and bacterial proteins against human MOG and MBP.
  • Identification of molecular similarities and conserved amino acid residues.

Main Results:

  • Identified associations between MBP and human parvovirus B19 (HPV-B19) and adeno-associated virus 4 (AAV-4).
  • Found similarities between MBP/MOG and antigens from various microbes (e.g., SARS-CoV-2, gut flora) and enzymes (e.g., bile salt hydrolase).
  • Observed identical amino acids at the active site of MBP and bile salt hydrolase, and conserved residues in MOG with WcfQ and Wzy enzymes.

Conclusions:

  • The study provides insights into the role of microbial antigens in MS pathogenesis.
  • Identified potential molecular mimicry targets for MS.
  • Suggests bioinformatics approaches for discovering new therapeutic strategies for CNS diseases like MS.