Novel Methods for Improved Identification Throughput and High-resolution Scoring for Proteomics

Download or read book Novel Methods for Improved Identification Throughput and High-resolution Scoring for Proteomics written by Brendan Keeley Faherty and published by . This book was released on 2012 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of proteomics aims to identify and quantify the protein contents of a biological sample. The mass spectrometer is the instrument of choice to characterize these proteins. In the typical proteomics experiment, mass spectra are collected from peptides as the peptides are eluted off of a liquid chromatography column and electrosprayed into the instrument as ions. Certain peptides are further selected as ions and isolated and fragmented. The fragments are recorded as tandem mass spectra, which are lists of fragment masses and intensities, and are subsequently used for identification. After the sample has been analyzed by the mass spectrometer, a number of methods, including database searching, can be used to match each tandem mass spectrum to a peptide that existed in the biological sample. Historically, the time to successfully identify the collected tandem mass spectra has been substantially longer than the time spent collecting them on the instrument. One of the standard database searching algorithms used for identification, SEQUEST, was published in 1994 when the time spent in data analysis was almost an afterthought since the number of collected spectra could be measured in the dozens. Today, modern mass spectrometers are capable of collecting thousands of tandem mass spectra each hour with orders and magnitude greater peak resolution. This thesis work builds on the SEQUEST algorithm and focuses on the use of high-resolution tandem mass spectra for the purposes of identification in order to allow more accurate and comprehensive identifications as well as novel methods to increase the throughput of the analysis of tandem mass spectra by database searching.