Developing strategies to identify peptide biomarker candidates for serological diagnostics

The occurrence of robust differences in antibody binding profiles of healthy individuals and those suffering from disease driven by an unknown antigen is established since more than two decades. Past research saw the application of several types of molecular libraries (e.g. cellular protein extracts, human proteins, random aptamers or peptides) to acquire antibody binding profiles. This lead to identification of characteristic binding profiles in various diseases including Thrombocytopenic Purpura, Systemic Lupus Erythematosus, Malaria, Autism, Sjögren-Syndrome, Multiple Sclerosis, Type I Diabetes, parasite infection, lung or brain tumorsand Alzheimer‘s. However, despite the knowledge on differential immunoprofiles, there are no validated biomarkers to date. The reason for this discrepancy lies in the chance nature of finding differential profiles. The detected between-profiles differences might be insufficient to allow for validation and translation into affordable medical products. Most importantly, being never thoroughly addressed, origin and base of differential profiles remain unknown; a circumstance which impedes optimization of molecular libraries and biomarker candidates. The proposed project aims at mastering those shortcomings by developing a novel strategy to identify peptide biomarker candidates whose binding characteristics sufficiently differ between case and control groups. Since there are no hypotheses as to how differential profiles emerge, the search for the strategy must be be explorative and data-driven. To establish a cost-minimizing strategy for biomarker identification, two groups with complementary expertise in computational prediction of peptide-antibody binding will work together to create a new dedicated binding profile data base and, based on this data base, devise new computational strategies and prediction tools to identify peptide biomarker candidates. We expect that the strategies generated during this project will contribute to the understanding of already existing but yet unexplained observations. Notably, the computational tools, strategies and biomarkers resulting from this project ought to have a significant impact on medicine and society, in that they will contribute to cost-minimizing biomarker search strategies and to a broader use of peptide biomarkers for serological diagnostics for which biomarkers are not yet known.

Or-Guil, Michal Dr. rer. nat. (Details) (Nachwuchsgruppe "Theoretische Immunologie")

German Israel Foundation

Projektstart: 01/2016
Projektende: 12/2018

Zuletzt aktualisiert 2020-20-03 um 23:05