Abstract
The design of protein conformational switches—or proteins that change conformations in response to a signal such as ligand binding—has great potential for developing novel biosensors, diagnostic tools, and therapeutic agents. Among the defining properties of such switches, the response time has been the most challenging to optimize. Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor in which the switching process occurs via mutually exclusive folding of two alternate frames. Notably, our strategy identifies mutations that increase switching rates by as much as 32-fold, achieving response times on the order of fast physiological Ca2+ fluctuations. Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
Highlights
The design of protein conformational switches—or proteins that change conformations in response to a signal such as ligand binding—has great potential for developing novel biosensors, diagnostic tools, and therapeutic agents
Circular permutation generally preserves the overall structure of a protein except for minor changes around the sites of permutation and linker addition, and previous NMR27 and circular dichroism[13] results suggested that the structures of WT and circular permutant (CP) calbindin are similar
While the main goal of this study was to assess the ability of contact scores derived from simulations of the WT switch constructs to predict positions where mutation improves the response time of the switch, we assessed how well our computational screen modeled the effect of mutations
Summary
The design of protein conformational switches—or proteins that change conformations in response to a signal such as ligand binding—has great potential for developing novel biosensors, diagnostic tools, and therapeutic agents. Response time has proven to be the most challenging of the switch properties to improve[3,10,11,12], e.g., the screening of hundreds of mutant switches in one study has achieved only a fourfold improvement in the response time[3] The reason for this difficulty is that the rational manipulation of the kinetics requires detailed views of the conformational switching pathways, including transition states that experiments typically cannot capture. Our strategy involves the use of molecular simulations that employ: (i) residue-level protein models that reproduce the expected mutually exclusive folding of individual switch components[14], and (ii) the weighted ensemble (WE) strategy[15,16], which enhances the sampling of rare events (e.g., protein folding) without biasing the dynamics These features enable qualitative predictions of promising mutations within 2 weeks. Because the WE strategy generates statistically unbiased pathways, the resulting rate constants are rigorous, and this property allows us to predict mutations that may improve the response time of the switch
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