Applications of Computational Protein Design

acetylcholine binding protein;agonist specificity;aldol condensation;aldolase;biosensor;cation-pi;disulfide bridge;double mutant cycle;enzyme design;ester hydrolysis;nicotinic acetylcholine receptor;protein design

Mao, Jessica ; Mayo, Stephen L.

University:California Institute of Technology

Department:Biology

关键词: acetylcholine binding protein;    agonist specificity;    aldol condensation;    aldolase;    biosensor;    cation-pi;    disulfide bridge;    double mutant cycle;    enzyme design;    ester hydrolysis;    nicotinic acetylcholine receptor;    protein design;   

Others  :  https://thesis.library.caltech.edu/595/1/JessicaMaoThesis.pdf

美国|英语

来源: Caltech THESIS

【 摘 要 】

Computational protein design determines the amino acid sequence(s) that will adopt a desired fold.It allows the sampling of a large sequence space in a short amount of time compared to experimental methods.Computational protein design tests our understanding of the physical basis of a protein’s structure and function, and over the past decade, has proven to be an effective tool.

We report the diverse applications of computational protein design with ORBIT (Optimization of Rotamers by Iterative Techniques).We successfully utilized ORBIT to construct a reagentless biosensor for nonpolar ligands on the maize non-specific lipid transfer protein, by first removing native disulfide bridges.We identified an important residue position capable of modulating the agonist specificity of the mouse muscle nicotinic acetylcholine receptor (nAChR) for its agonists: acetylcholine, nicotine, and epibatidine.Our efforts on enzyme design produced a lysozyme mutant with ester hydrolysis activity, while progress was made toward the design of a novel aldolase.

Computational protein design has proven to be a powerful tool for the development of novel and improved proteins.As we gain a better understanding of proteins and their functions, protein design will find many more exciting applications.