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

Abstract

Protein optoelectronics is an emerging field facing implementation and stabilization challenges of proteins in harsh non-natural environments, such as dry polymers, inorganic materials, etc., operating at high temperatures/irradiations. In this context, additives promoting structural and functional protein stabilization are paramount to realize highly performing devices. On one hand, trial-error experimental assays based on previous knowledge of classical additives in aqueous solutions are effort/time-consuming, while their translation to water-less matrices is uncertain. On the other hand, computational simulations (molecular dynamics, electronic structure methods, etc.) are limited by the system size and time. Herein, ligand-binding affinity and atomic perturbations to create a day-fast computational method combining Vina And Rosetta for Protein Additives (VARPA) to simulate the stabilization effect of sugars for the archetypal enhanced green fluorescent protein embedded in a standard dry polymer color-converting filter for bio-hybrid light-emitting diodes is merged. The VARPA's sugar additive prediction trend for protein stabilization is nicely validated by thermal and photophysical studies as well as lighting device analysis. The device stability followed the predicted enhanced stability trend, reaching a 40-fold improvement compared to reference devices. Overall, VARPA can be adapted to a myriad of additives and proteins, driving first-step experimental efforts toward highly performing protein devices.