VARPA: In Silico Additive Screening for Protein-Based Lighting Devices.

Area of Science:

• Protein optoelectronics
• Bio-hybrid devices
• Materials science

Background:

• Protein stabilization in non-natural environments is crucial for device performance.
• Traditional methods for identifying protein stabilizers are time-consuming and uncertain.
• Computational simulations are limited by system size and simulation time.

Purpose of the Study:

• To develop a rapid computational method for predicting protein stabilizers.
• To simulate the stabilization effect of sugars on enhanced green fluorescent protein (eGFP).
• To assess the performance of protein-based devices with predicted stabilizers.

Main Methods:

• Developed VARPA (Vina And Rosetta for Protein Additives), a computational method combining ligand-binding affinity and atomic perturbation simulations.
• Simulated the effect of sugar additives on eGFP embedded in a dry polymer matrix.
• Validated computational predictions with thermal, photophysical, and device performance studies.

Main Results:

• VARPA successfully predicted the stabilizing effects of sugar additives.
• Experimental studies validated VARPA's predictions.
• Bio-hybrid light-emitting diodes incorporating stabilized eGFP showed a 40-fold improvement in stability.

Conclusions:

• VARPA offers a fast and adaptable approach for identifying protein stabilizers.
• The method can accelerate the development of high-performing protein-based devices.
• VARPA can be applied to various additives and proteins for diverse applications.