posted on 2005-04-11, 00:00authored byBrian C. Searle, Surendra Dasari, Phillip A. Wilmarth, Mark Turner, Ashok P. Reddy, Larry L. David, Srinivasa R. Nagalla
Algorithms that can robustly identify post-translational protein modifications from mass spectrometry
data are needed for data-mining and furthering biological interpretations. In this study, we determined
that a mass-based alignment algorithm (OpenSea) for de novo sequencing results could identify post-translationally modified peptides in a high-throughput environment. A complex digest of proteins from
human cataractous lens, a tissue containing a high abundance of modified proteins, was analyzed
using two-dimensional liquid chromatography, and data was collected on both high and low mass
accuracy instruments. The data were analyzed using automated de novo sequencing followed by
OpenSea mass-based sequence alignment. A total of 80 modifications were detected, 36 of which were
previously unreported in the lens. This demonstrates the potential to identify large numbers of known
and previously unknown protein modifications in a given tissue using automated data processing
algorithms such as OpenSea.
Keywords: proteomics • mass spectrometry • protein identification • bioinformatics • de novo sequencing • mass-based alignment • post-translational modification • human lens • crystallin • cataract