Multivalency Enables Signal Processing at Single Protein Level

Area of Science:

• Biotechnology
• Molecular Engineering
• Synthetic Biology

Background:

• Synthetic signal processing in cells can utilize complex molecular networks or simpler single-molecule mechanisms.
• Single-molecule processors offer reduced genetic load and easier delivery, with multivalent protein binders exhibiting unique behaviors based on cell antigen profiles.

Purpose of the Study:

• To address the lack of quantitative methods for designing multivalent interactions on cell surfaces.
• To develop a computational tool for guiding the design of multivalent proteins for cell surface binding and signal processing.

Main Methods:

• Development of the Multivalent Antigen Sensing Simulator (MASS) computational model.
• Validation of the MASS model through in vitro and cell binding experiments.

Main Results:

• The MASS model accurately predicted the design of multivalent binders for sensing cell surface antigen identities and enabling selective cell killing.
• Experimental verification confirmed the model's ability to capture the nonmonotonic relationship between valency and monovalent affinity in sensing antigen densities.
• The model demonstrated predictive accuracy in designing binders that simultaneously sense both antigen identity and density.

Conclusions:

• The developed MASS model provides practical guidelines for designing multivalent proteins with specific cell-sensing capabilities.
• The simulator enables rapid and precise in silico prescreening of multivalent protein binders for various applications.