Statistical pattern matching facilitates the design of polyvalent inhibitors of anthrax and cholera toxins

Abstract

Numerous biological processes involve the recognition of a specific pattern of binding sites on a target protein or surface. Although ligands displayed by disordered scaffolds form stochastic rather than specific patterns, theoretical models predict that recognition will occur between patterns that are characterized by similar or "matched" statistics. Endowing synthetic biomimetic structures with statistical pattern matching capabilities may improve the specificity of sensors and resolution of separation processes. We demonstrate that statistical pattern matching enhances the potency of polyvalent therapeutics. We functionalized liposomes with an inhibitory peptide at different densities and observed a transition in potency at an interpeptide separation that matches the distance between ligand-binding sites on the heptameric component of anthrax toxin. Pattern-matched polyvalent liposomes inhibited anthrax toxin in vitro at concentrations four orders of magnitude lower than the corresponding monovalent peptide, and neutralized this toxin in vivo. Statistical pattern matching also enhanced the potency of polyvalent inhibitors of cholera toxin. This facile strategy should be broadly applicable to the detection and neutralization of toxins and pathogens.