Unknown

Dataset Information

0

De novo design of modular and tunable protein biosensors.


ABSTRACT: Naturally occurring protein switches have been repurposed for the development of biosensors and reporters for cellular and clinical applications1. However, the number of such switches is limited, and reengineering them is challenging. Here we show that a general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which the binding of a peptide key triggers biological outputs of interest2. The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; analyte binding drives the switch from the closed to the open state. Because the sensor is based on the thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We create biosensors that can sensitively detect the anti-apoptosis protein BCL-2, the IgG1 Fc domain, the HER2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac troponin I and an anti-hepatitis B virus antibody with the high sensitivity required to detect these molecules clinically. Given the need for diagnostic tools to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)3, we used the approach to design sensors for the SARS-CoV-2 spike protein and antibodies against the membrane and nucleocapsid proteins. The former, which incorporates a de novo designed spike receptor binding domain (RBD) binder4, has a limit of detection of 15 pM and a luminescence signal 50-fold higher than the background level. 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.

SUBMITTER: Quijano-Rubio A 

PROVIDER: S-EPMC8074680 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC10312586 | biostudies-literature
| S-EPMC7072037 | biostudies-literature
| S-EPMC5497568 | biostudies-literature
| S-EPMC10115654 | biostudies-literature
| S-EPMC6733528 | biostudies-literature
| S-EPMC6701466 | biostudies-literature
| S-EPMC2841848 | biostudies-literature
| S-EPMC7397813 | biostudies-literature
| S-EPMC8404036 | biostudies-literature
| S-EPMC10697138 | biostudies-literature