Computational and experimental assessment of backbone templates for computational protein design

Abstract

Computational protein design has taken big strides over the recent years, however, the tools available are still not at a state where a sequence can be designed to fold into a given protein structure at will and with high probability. We have here applied a recent release of Rosetta Design to redesign a set of structurally very similar proteins belonging to the Thioredoxin fold. We determined design success using a combination of a genetic screening tool to assay folding/stability in E. coli and selecting the best hits from this for further biochemical characterization. We have previously used this set of template proteins for redesign and found that success was highly dependent on template structure, a trait which was also found in this study. Nevertheless, state of the art design software is now able to predict the best template, most likely due to the introduction of the cart_bonded energy term. The template that led to the greatest fraction of successful designs was the same (a Thioredoxin from spinach) as that identified in our previous study. Our previously described redesign of Thioredoxin, which also used the spinach protein as template, however also performed well. In the present study, both these templates yielded proteins with compact folded structures, and enforces the conclusion that any design project must carefully consider different design templates. Fortunately, selecting designs using the cart_bonded energy term appears to correctly identify such templates.