Computational and structural approaches for the design of green fluorescent protein-based biosensors

Authors
Pitman, Derek James
ORCID
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Other Contributors
Bystroff, Christopher, 1960-
Cramer, Steven M.
Collins, Cynthia H.
García, Angel E.
Makhatadze, George I.
Issue Date
2014-05
Keywords
Biochemistry and biophysics
Degree
PhD
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
Computational and experimental studies are presented with the goal of improving and simplifying the design process. First, a modification to the energy function of the design algorithm is described which optimizes core packing, suggesting the creation of a tighter binding interface. Second, a new computational algorithm is presented which attempts to quantify changes in void volume morphology with the goal of understanding the relationship between core packing and binding affinity in an immobilized setting. Third, a general computational protein design approach is developed which splits a given design problem into smaller disjoint problems that can be computed independently in isolation. This new design scheme not only computes existing designs more quickly with minimal losses in optimality but also allows for the computation of designs too complex to reasonably run on the same computational resources. Lastly, an experimental study which introduced disulfide bonds into the GFP loop regions is reported. This disulfide engineering experiment was intended to use rational unfolding pathway-based hypotheses to stabilize GFP in the leave-one-out state, but eventually produced new information about its folding pathway. The final chapter of this thesis considers future directions for applications of the leave-one-out design approach and other uses for GFP in biotechnology.
Description
May 2014
School of Science
Department
Biochemistry and Biophysics Program
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
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