Open Collections

Redesign of the N-end rule protein ClpS for use in high-throughput N-end protein sequencing

University of British Columbia

Current protein sequencing methods include mass spectrometry and Edman degradation. We envision a novel high-throughput protein sequencing method using affinity adapters to recognize the N-terminal residue of a denatured peptide in an iterative process. This thesis takes a first step toward designing robust and selective affinity reagents. We outline our pipeline for designing selective protein adapters that recognize the N-terminal amino acid of a peptide independent of the following sequence. We based our design on a substrate recognition protein in the N-end rule pathway, ClpS. The bacterial N-recognin protein ClpS binds peptide substrates, termed N-degrons, that have a bulky hydrophobic amino acid (L/F/Y/W) at the N-terminus. Using full atom in silico models we designed hydrogen bonding and salt-bridge contacts in ClpS to novel N-degron substrates (N-end D/E/T), predicted the selectivity of these designs, and experimentally verified them. Of 11 designs, we purified nine that were soluble by SDS-PAGE, and obtained a peptide binding profile to 30 peptides with a modified ELISA assay. Most designs were non-specific or had no binding affinity. Four designs M53A, L112F, I45L, I45L_I45L_M53A had an increase in affinity to various substrates, but were not selective as they retained affinity to the native substrates (N-end L/F/Y/W). We performed molecular dynamics simulations on several proteins that were soluble or insoluble under standard expression conditions in E. coli, in order to learn parameters that were indicative of kinetic instability. Using a back-to-consensus approach, we identified a point mutant S104F that stabilizes the scaffold of ClpS as assayed by GFP fluorescence in a GFP-ClpS fusion protein. This thesis outlines the computational design pipeline we developed, which includes a RosettaScripts protocol, an in silico selectivity screen with AutoDock, and a kinetic stability confidence score from a molecular dynamics trajectory. Finally, we make suggestions toward designing selective affinity reagents for high-throughput N-end protein sequencing.

Text

2014-04-11

Attribution 2.5 Canada

http://hdl.handle.net/2429/46377

Genome Science and Technology

University of British Columbia

UBCV

http://creativecommons.org/licenses/by/2.5/ca/