Using Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold Recognition

The 3D structures of proteins may provide important clues to their functions and roles in complex biological pathways. Traditional methods such as X-ray crystallography and NMR are not feasible for all proteins, while theoretical models are typically not validated by experimental data. This proj...

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Main Author: Mak, Esther W. M.
Format: Others
Language:en
Published: University of Waterloo 2006
Subjects:
Online Access:http://hdl.handle.net/10012/1228
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-OWTU.10012-12282013-10-04T04:07:19ZMak, Esther W. M.2006-08-22T14:41:50Z2006-08-22T14:41:50Z20062006http://hdl.handle.net/10012/1228The 3D structures of proteins may provide important clues to their functions and roles in complex biological pathways. Traditional methods such as X-ray crystallography and NMR are not feasible for all proteins, while theoretical models are typically not validated by experimental data. This project investigates the use of chemical crosslinkers as an experimental means of validating these models. Five target proteins were successfully purified from yeast whole cell extract: Transketolase (TKL1), inorganic pyrophosphatase (IPP1), amidotransferase/cyclase HIS7, phosphoglycerate kinase (PGK1) and enolase (ENO1). These TAP-tagged target proteins from yeast <em>Saccharomyces cerevisiae</em> allowed the protein to be isolated in two affinity purification steps. Subsequent structural analysis used the homobifunctional chemical crosslinker BS<sup>3</sup> to join pairs of lysine residues on the surface of the purified protein via a flexible spacer arm. Mass spectrometry (MS) analysis of the crosslinked protein generated a set of mass values for crosslinked and non-crosslinked peptides, which was used to identify surface lysine residues in close proximity. The Automatic Spectrum Assignment Program was used to assign sequence information to the crosslinked peptides. This data provided inter-residue distance constraints that can be used to validate or refute theoretical protein structure models generated by structure prediction software such as SWISS-MODEL and RAPTOR. This approach was able to validate the structure models for four of the target proteins, TKL1, IPP1, HIS7 and ENO1. It also successfully selected the correct models for TKL1 and IPP1 from a protein model library and provided weak support for the HIS7, PGK1 and ENO1 models.application/pdf1417782 bytesapplication/pdfenUniversity of WaterlooCopyright: 2006, Mak, Esther W. M.. All rights reserved.BiologyChemical crosslinkingmass spectrometryprotein model validationfold recognitionUsing Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold RecognitionThesis or DissertationBiologyMaster of Science
collection NDLTD
language en
format Others
sources NDLTD
topic Biology
Chemical crosslinking
mass spectrometry
protein model validation
fold recognition
spellingShingle Biology
Chemical crosslinking
mass spectrometry
protein model validation
fold recognition
Mak, Esther W. M.
Using Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold Recognition
description The 3D structures of proteins may provide important clues to their functions and roles in complex biological pathways. Traditional methods such as X-ray crystallography and NMR are not feasible for all proteins, while theoretical models are typically not validated by experimental data. This project investigates the use of chemical crosslinkers as an experimental means of validating these models. Five target proteins were successfully purified from yeast whole cell extract: Transketolase (TKL1), inorganic pyrophosphatase (IPP1), amidotransferase/cyclase HIS7, phosphoglycerate kinase (PGK1) and enolase (ENO1). These TAP-tagged target proteins from yeast <em>Saccharomyces cerevisiae</em> allowed the protein to be isolated in two affinity purification steps. Subsequent structural analysis used the homobifunctional chemical crosslinker BS<sup>3</sup> to join pairs of lysine residues on the surface of the purified protein via a flexible spacer arm. Mass spectrometry (MS) analysis of the crosslinked protein generated a set of mass values for crosslinked and non-crosslinked peptides, which was used to identify surface lysine residues in close proximity. The Automatic Spectrum Assignment Program was used to assign sequence information to the crosslinked peptides. This data provided inter-residue distance constraints that can be used to validate or refute theoretical protein structure models generated by structure prediction software such as SWISS-MODEL and RAPTOR. This approach was able to validate the structure models for four of the target proteins, TKL1, IPP1, HIS7 and ENO1. It also successfully selected the correct models for TKL1 and IPP1 from a protein model library and provided weak support for the HIS7, PGK1 and ENO1 models.
author Mak, Esther W. M.
author_facet Mak, Esther W. M.
author_sort Mak, Esther W. M.
title Using Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold Recognition
title_short Using Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold Recognition
title_full Using Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold Recognition
title_fullStr Using Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold Recognition
title_full_unstemmed Using Chemical Crosslinking and Mass Spectrometry for Protein Model Validation and Fold Recognition
title_sort using chemical crosslinking and mass spectrometry for protein model validation and fold recognition
publisher University of Waterloo
publishDate 2006
url http://hdl.handle.net/10012/1228
work_keys_str_mv AT makestherwm usingchemicalcrosslinkingandmassspectrometryforproteinmodelvalidationandfoldrecognition
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