Computational design of specific binding proteins using Leave-One-Out The goal of this research is to design a receptor protein to bind any protein target. Furthermore, the binding event will be signaled by the appearance of fluorescence. The novel binding protein will be able to sense and report the presence of a specific protein or peptide in a mixture of others, allowing the detection of any disease agent or protein of interest. The new approach takes advantage of the green fluorescent protein (GFP) what we know about its folding pathway. When GFP folds, it does in a specified order of events called a pathway. When it finishes folding, its fluorescence activity is immediately turned on. If we leave out one small piece of GFP so that the folding cannot finish folding, then it sits in an inactive state until the missing piece appears. Using this Leave-One-Out strategy, partially folded proteins become sensors for their missing pieces. Using computational design algorithms, a new amino acid sequence can be substituted for the missing piece, making the designed GFP a sensor for the new sequence. But accurate computational protein design is challenging because of inherent assumptions. Two approaches are proposed to overcome the weaknesses. First, thousands of candidates will be designed, synthesized in yeast and then screened for their biosensor function using high throughput cell sorting technology. Second, more knowledge about the folding pathway will be generated by pulse-labeling the protein as it folds, then finding out what parts of the protein fold first. This will improve the computational model for folding, and therefore improve the ability to design partially folded leave-one-out biosensors. A cautious, step-wise design strategy is proposed for screening, so that every experiment tests a specific hypothesis about GFP folding and function. A known drawback of the leave-one-out method is the necessity of a having a partially unfolded off-state protein that can aggregate an cause problems. To fix this, biosensor proteins will be genetically fused to a fiber-forming protein to create robust and stable biosensor fabrics that no longer have a problem with aggregation. The final product of this research will be is a silk-like biosensor fabric that is computationally designed to sense any protein target and glow green when the target is present.
Computationally designed ?uorescent biosensors based on green ?uorescent protein will be able to detect proteins from dengue and zika viruses in vitro, helping to prevent their spread. The Leave-One-Out design method allow the folding of the sensor protein to signal the presence of a desired target. By genetically fusing the biosensors to the ?ber-forming protein Ubx, we will create durable and reusable biosensor materials.
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