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Toward Computationally Designed Self-Reporting Biosensors Using Leave-One-Out Green Fluorescent Protein
Yao-Ming Huang1, Shounak Banerjee, Donna E Crone
1Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco , San Francisco, California 94158, United States.
Biochemistry
|September 24, 2015
Summary
Computational protein design created a modified green fluorescent protein (GFP) that binds an influenza peptide. Directed evolution improved this binding, though full fluorescence reconstitution was not achieved.
Area of Science:
- Protein Engineering
- Biochemistry
- Computational Biology
Background:
- Leave-one-out green fluorescent protein (LOOn-GFP) is a truncated GFP variant.
- LOO7-GFP reconstitutes fluorescence upon addition of exogenous β-strand 7 (S7).
- Computational design can modify LOOn-GFP to accept alternative peptide sequences.
Purpose of the Study:
- To computationally design a LOOn-GFP variant capable of binding a peptide from the H5N1 influenza virus hemagglutinin (HA).
- To characterize the binding properties and fluorescence reconstitution of the designed LOOn-GFP-HA variant.
- To improve peptide binding and fluorescence reconstitution through directed evolution.
Main Methods:
- Utilized DEEdesign software to generate a library of mutated LOO7-GFP sequences.
- Coexpressed the designed library with the HA peptide in E. coli and screened for fluorescence.
- Purified and characterized promising variants using biochemical and biophysical methods.
- Employed in vitro evolution to further optimize peptide binding and fluorescence.
Main Results:
- A computationally designed variant, LOO7-HA4, was generated with 7 mutations, exhibiting folding, fluorescence, and HA peptide binding.
- Peptide binding induced dissociation of a novel oligomeric complex, decreasing fluorescence instead of promoting reconstitution.
- Directed evolution enhanced HA peptide binding affinity significantly, though complete fluorescence reconstitution remained elusive.
- The ratio of HA to S7 binding increased from 0.0 (wild-type) to 0.01 (computational design) and 0.48 (directed evolution).
Conclusions:
- Computational protein design successfully created a LOOn-GFP variant that binds an influenza HA peptide.
- Directed evolution is a viable strategy to enhance peptide binding affinity in engineered proteins.
- The study revealed a novel, glowing oligomeric complex formed by the engineered protein, distinct from native folding pathways.
- While full fluorescence reconstitution was not achieved, the engineered system demonstrates potential for peptide-responsive protein applications.
