COMPUTATIONAL DESIGN AND EXPERIMENTAL CHARACTERIZATION OF PROTEINS WITH NOVEL FUNCTIONS
Open Access
- Author:
- Fazelinia, Hossein
- Graduate Program:
- Chemical Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- August 28, 2009
- Committee Members:
- Costas D Maranas, Dissertation Advisor/Co-Advisor
Costas D Maranas, Committee Chair/Co-Chair
Patrick Cirino, Committee Chair/Co-Chair
David D Boehr, Committee Member
Andrew Zydney, Committee Member - Keywords:
- OptGraft
Protein engineering
Computational protein design
Enzyme cofactor alteration
IPRO - Abstract:
- Protein engineering involves the design of known protein structures to introduce an improved or completely novel function. This is accomplished by either modifying the existing structure (i.e., redesign) to achieve an altered functionality or by introducing a completely new binding site. In this thesis computational modeling is first tested by altering the effector binding specificity of the bacterial transcriptional regulatory protein AraC to molecules other than L-arabinose. A systematic computational formulation was developed and employed to favor the binding of a targeted ligand while suppressing the binding energy of decoy molecules. Next we introduce a modified version of IPRO equipped with different implicit solvation modules to redesign Candida boidinii xylose reductase (CbXR) to use NADH as its cofactor by finding the optimal set of mutations in the CbXR binding pocket. Calculated cofactor binding energy was verified as a good surrogate to computationally drive cofactor alteration. We performed site-directed mutagenesis to redesign CbXR according to the designs predicted by IPRO. Experimental results for predicted mutants as well as control studies quantitatively demonstrated the value of using computations to guide protein redesign for altered cofactor usage. Finally we present the computational procedure OptGraft for placing a novel binding pocket onto a protein structure so as its geometry is minimally perturbed. This was accomplished by introducing a two-level procedure where we first identify where are the most appropriate locations to graft the new binding pocket into the protein fold by minimizing the departure from a set of geometric restraints using mixed-integer linear optimization. Upon identifying the suitable locations that can accommodate the new binding pocket CHARMM energy calculations were employed to identify what mutations in the neighboring residues, if any, are needed to ensure that the minimum energy conformation of the binding pocket conserves the desired geometry. OptGraft was successfully used to guide our experimental studies for transferring a calcium binding pocket from thermitase protein (PDB:1thm) into the first domain of CD2 protein (PDB:1hng).