Open AccessCharacterization of N-terminal processing of group VIA phospholipase A2 and of potential cleavage sites of amyloid precursor protein constructs by automated identification of signature peptides in LC/MS/MS analyses of proteolytic digests
Author(s) -
Houyan Song,
Silva Hečimović,
Alison M. Goate,
FongFu Hsu,
Shunzhong Bao,
Ilan Vidavsky,
Sasanka Ramanadham,
John Turk
Publication year - 2004
Publication title -
journal of the american society for mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.961
H-Index - 127
eISSN - 1879-1123
pISSN - 1044-0305
DOI - 10.1016/j.jasms.2004.08.012
Subject(s) - chemistry , proteolysis , amyloid precursor protein , gene isoform , peptide , biochemistry , proteolytic enzymes , amyloid beta , computational biology , alzheimer's disease , enzyme , biology , gene , medicine , disease , pathology
Dysregulation of proteolytic processing of the amyloid precursor protein (APP) contributes to the pathogenesis of Alzheimer's Disease, and the Group VIA phospholipase A(2) (iPLA(2)beta) is the dominant PLA(2) enzyme in the central nervous system and is subject to regulatory proteolytic processing. We have identified novel N-terminal variants of iPLA(2)beta and previously unrecognized proteolysis sites in APP constructs with a C-terminal 6-myc tag by automated identification of signature peptides in LC/MS/MS analyses of proteolytic digests. We have developed a Signature-Discovery (SD) program to characterize protein isoforms by identifying signature peptides that arise from proteolytic processing in vivo. This program analyzes MS/MS data from LC analyses of proteolytic digests of protein mixtures that can include incompletely resolved components in biological samples. This reduces requirements for purification and thereby minimizes artifactual modifications during sample processing. A new algorithm to generate the theoretical signature peptide set and to calculate similarity scores between predicted and observed mass spectra has been tested and optimized with model proteins. The program has been applied to the identification of variants of proteins of biological interest, including APP cleavage products and iPLA(2)beta, and such applications demonstrate the utility of this approach.