In 2007, pioneering experiments by Carlson et al. [1] revealed that multivalent targeting vectors equipped with weak ligands could effectively kill cells over-expressing specific receptors while sparing those with normal receptor levels. This contrasted with mono-valent delivery vectors containing a single strong-binding targeting ligand, which cannot achieve such discrimination, and therefore necessarily cause collateral damage. The findings of Carlson et al. attracted much attention because receptor over-expression is a hallmark of cancer: multivalent drug-delivery vectors might therefore make it possible to eliminate diseased cells while minimizing harm to healthy cells.

A possible rationalisation of these results was provided in 2010 by Martinez-Veracoechea and Frenkel [2], who used statistical mechanical theory and simulations to show that binding of a ligand-functionalised vector to a receptor-coated target was strongly affected by the combinatorial entropy of bond formation. In multivalent systems, highly non-linear effects cause the binding probability to exhibit an almost perfect on-off behavior, being nearly zero below a certain receptor threshold concentration, and 100% above it: such switch-like behavior due to the effect of combinatorial entropy is termed “super-selectivity”.  
Initial experimental work based on ref [2] focused on the design of synthetic targeting vectors [3,4]. However, recently it has become apparent that our immune system  may also exploit superselectivity. It should be noted that immunologists have long been aware of the importance of multivalency, for example in the activation of B and T cells, by B/T receptors (BCR/TCR), thereby overcoming thresholds of activation present for lower affinity receptor-antigen interactions [5-7] often found before receptor maturation. Yet the relation between superselectivity and “on-off” switching has remained largely untested in immunology.  

Recent work suggests that it is not just the increase in binding strength, but the highly non-linear nature of this increase that can control the switch-like behavior of immune response. The step-like shape of super-selective binding curves suggests why immune cells have evolved mechanisms to tune membrane BCR (and TCR) levels over a broad range of concentrations. Moreover, super-selective binding may explain how the immune system is able to fine-tune its response to foreign antigen, while avoiding activation against self. In anergic self-reactive B cells, downregulation of the expression of BCR enables the self-reactive B cells to ignore the self-antigen [8,9], unless this self-antigen happens to form a multivalent array [10]. Super-selective fine-tuning is influenced by receptor clustering due to inter-receptor attraction, and the size and valency of the multivalent agent that B and T cells must recognize for activation, such as viruses or other cells.

In the context of this proposal, it is important to note that, even though the biomolecular interactions responsible for, say, antibody-antigen binding are highly specific, the principles behind super-selectivity are generic and can be modelled at a more coarse-grained level. In fact, good agreement between experiments and simulations can be obtained with relatively simple coarse-grained models [3,4,11-14]. For example, super-selective responses have already been successfully investigated using this modelling strategy both for fully-synthetic model systems, e.g., binding of multivalent polymers [3] or DNA-coated colloids [14] to surfaces, as well as for more complex ones involving biological elements, such as nanoparticles binding to cells over-expressing cognate receptors [4], or the binding and activation of  antimicrobial peptide-DNA complexes to Toll-like-receptors [11]. In fact, ongoing research combining experiments with modelling has also recently confirmed super-selective effects involving BCR [13], and there are strong hints that TCR similarly displays such effects [15-17], further stressing the potential for super-selectivity to provide a rather general mechanism for understanding immune responses.

By bringing together Soft Matter modellers, theoreticians and Immunologists, the proposed workshop aims to increase the synergy between these vibrant fields of research. If successful, it is likely that the workshop will stimulate new, joint research in immunology and in simulation.