Computational models of B cell and T cell receptors

Abstract

We review computational models of B cell and T cell receptors. We first consider string models where both antigen specific receptors on immune cells and antigens are represented by binary strings, or more generally, digit strings with a given number of letters. Various match rules are presented to describe the binding interaction between receptors and antigens. A second class of models is geometric models where receptors and antigens are represented as geometric shapes. A rule of interaction among receptors in shape space is introduced. Lastly, the random energy model is introduced where the binding interaction between receptors and antigens is quantified with an energy function derived from the physics of protein interaction. To compare these approaches, we explicitly calculate how receptor-ligand affinity is affected by a point mutation in different models. These calculations are relevant to understanding the correlation between the change in the sequence and the change in the binding strength. We finally review a method for connecting string models and shape space models in the context of analyzing antibody binding assay data relevant to the immune response against the influenza virus.