Computational design of a modular protein sense-response system

Area of Science:

• Protein Engineering
• Synthetic Biology
• Computational Biology

Background:

• Living systems fundamentally sense and respond to signals.
• Despite advances in protein design, engineering new protein sensors remains challenging.
• A generalizable computational approach for arbitrary protein sensor design is lacking.

Purpose of the Study:

• To develop a generalizable computational strategy for designing novel sensor-actuator proteins.
• To create protein sensors capable of detecting specific small molecules.
• To demonstrate the functionality of engineered sensors in vitro and in cellular environments.

Main Methods:

• Designed de novo binding sites within heterodimeric protein-protein interfaces.
• Coupled ligand sensing to modular protein actuation using split reporters.
• Utilized computational modeling to guide the design of protein structures and binding pockets.

Main Results:

• Successfully designed and engineered protein sensors that respond to farnesyl pyrophosphate.
• Demonstrated sensor functionality both in vitro and within living cells.
• Validated the computational design by confirming the crystal structure of the engineered binding site matched the model.

Conclusions:

• The developed computational strategy provides a generalizable method for engineering new protein sensors.
• This approach facilitates the creation of biosensors for metabolic intermediates like farnesyl pyrophosphate.
• The strategy opens new possibilities for linking biological outputs to diverse chemical signals.