De novo design of modular and tunable allosteric biosensors

Abstract

Naturally occurring allosteric protein switches have been repurposed for developing novel biosensors and reporters for cellular and clinical applications 1, but the number of such switches is limited, and engineering them is often challenging as each is different. Here, we show that a very general class of allosteric protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which binding of a peptide key triggers biological outputs of interest 2. Using broadly applicable design principles, we allosterically couple binding of protein analytes of interest to the reconstitution of luciferase activity and a bioluminescent readout through the association of designed lock and key proteins. Because the sensor is based purely on thermodynamic coupling of analyte binding to switch activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We demonstrate the modularity of this platform by creating biosensors that, with little optimization, sensitively detect the anti-apoptosis protein Bcl-2, the hIgG1 Fc domain, the Her2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac Troponin I and an anti-Hepatitis B virus (HBV) antibody that achieve the sub-nanomolar sensitivity necessary to detect clinically relevant concentrations of these molecules. Given the current need for diagnostic tools for tracking COVID-19 3, we use the approach to design sensors of antibodies against SARS-CoV-2 protein epitopes and of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The latter, which incorporates a de novo designed RBD binder, has a limit of detection of 15pM with an up to seventeen fold increase in luminescence upon addition of RBD. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.