| Protein-based biosensors have been designed to detect changes in biological events based on the principle of fluorescence resonance energy transfer (FRET). These biosensors generally have weak dynamic ranges that are undesirable for applications such as high throughput drug screening. Hence, I introduced a computational modeling approach to improve the dynamic range of a FRET protein biosensor. Next, to systemize this approach, I developed a modeling tool called Fusion Protein MODeller (FPMOD) that constructs the biosensor models and predicts their FRET properties. Lastly, I developed a molecular biology technique to systematically construct a library of circularly permutated yellow fluorescent proteins. This technique can be used to maximize the dynamic range of FRET protein biosensors. Together, this work represents an advance in the design, simulation and optimization of protein-based FRET biosensors. |
