A computational approach to matching multiple sclerosis-related, IGH CDR3s with a MBP epitope.

Abstract

In multiple sclerosis (MS), T-cell receptors (TCRs) and antibodies specifically target the main structural proteins of myelin, including myelin basic protein (MBP), especially a specific, canonical, immunoglobulin (IG)-targeted MBP epitope. Efficient computational analyses to diagnose or monitor autoimmune conditions, which could have broad applicability in clinical trials or in diagnoses, remains a challenge. As such, we considered the possibility that focusing on the immunoglobin heavy chain (IGH) complementarity determining region-3 (CDR3) amino acid sequences could support the development of an efficient, convenient, and user-friendly approach to detecting or assessing IGH targets in MS. Thus, we applied a chemical complementarity scoring algorithm, extensively benchmarked in many cancer settings, to assess the combined electrostatic and hydrophobic attractiveness of large numbers of (individual patient) IGH CDR3s and the canonical IG MBP epitope. Samples and controls were filtered to only include CDR3s above a baseline chemical complementarity score. Then, the frequency of each unique IGH CDR3 (with the minimum MBP epitope complementarity) in the MS samples was compared to the same parameter for the control sample. Specifically, a greater number of high frequency IGH CDR3s, with chemically complementary to the canonical MBP epitope, was detected in 47 out of 48 MS-control comparisons, in most cases representing a p < 0.0001. With continued development, this approach has the potential to lead to a user-friendly computational screening tool for patients at risk for developing MS. Additional results indicate that the methodology could also be applied to antigen epitope discovery.