Computational modeling – an approach to the development of blood grouping reagents

ABSTRACT

Introduction: Blood group antigens are defined by an immune response that generates antibodies against a red blood cell molecule. Antibodies against these antigens can be associated with hemolytic transfusion reactions. However, difficulties can arise when developing antibodies against antigens through the use of peptide sequences alone. Three-dimensional representations (models) of the molecular structure of antigen-bearing proteins can provide valuable insights into tertiary structures and their consequent antigenicity. This can be achieved through predictive computational modeling to produce both structural and molecular dynamics models of blood group proteins.

Areas covered: Authors discuss the use of molecular dynamic simulations on existing structures, as well as the use of computational modeling techniques in the development of protein models lacking preexisting data. Finally, the authors discuss specific examples of the use of computationally derived models of the MNS blood group system and its use in attempts to produce antibodies against MNS proteins.

Expert opinion: Although in silico techniques have limitations, computer-based predictive models can inform the direction of research into blood group proteins. It is to be expected that as computer-based techniques grow more powerful these contributions will be even more significant.

KEYWORDS:

• In silico
• computer modeling
• MNS
• blood group protein
• blood group antigen
• antibody development

Article highlights

• Examples provided of the use of computational modeling for molecular dynamic simulations of existing blood group structures associated with antigens

• Examples provided for the development of in silico only structural models where experimental data are limited or non-existent.

• Discussion of how computational models can be used to better understand protein interactions and epitopes with the potential to explore their usefulness in blood grouping.

• Discussion of how results from predicted protein structures can assist in identifying epitopes for improvement of antibody development against BGAs.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers in this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was supported by the ARC Training Centre for Biopharmaceutical Innovation (CBI) from the Australian Research Council (ARC). Australian Governments fund Australian Red Cross Lifeblood for the provision of blood, blood products and services to the Australian community.