Hydroxyproline-containing proteins (other than collagens) are rare and difficult to identify. Only 14 such proteins have been found in the human proteome by biochemical methods, despite the fact that the… Click to show full abstract
Hydroxyproline-containing proteins (other than collagens) are rare and difficult to identify. Only 14 such proteins have been found in the human proteome by biochemical methods, despite the fact that the list includes examples of biological importance such as Hypoxia-inducible factor and the 40S ribosomal protein S23 (RPS23), both of which have significant biological function of the post-translational modification. Comparison of multi-notch search software Global-PTM-Discovery to conventional proteomic database search software gave a nine-fold improvement in correctly identifying non-collagen peptides containing hydroxyproline. 36 unique peptides representing 24 unique hydroxyproline sites in 21 proteins were discovered, of which only Pro62 of RPS23 had been reported previously in UniProt. Eight of the sites were found to be conserved as prolines in nine species examined, ranging from human to yeast. These include sites 51 and 395 in Protein disulfide-isomerase (PDIA1), and sites 204 and 553 in Protein disulfide-isomerase A4 (PDIA4). The apparent occupancy of these sites ranged from 72-89 % suggesting a structural and possibly functional role of these PTMs. Fifteen of the sites probably contain 4R-hydroxyproline (Pro30 of Serpin H1, Pro520 of Aspartyl/asparaginyl beta-hydroxylase, Pro223 of Neutral alpha-glucosidase AB, Pro977 of Hypoxia up-regulated protein 1, Pro378 of Protein ERGIC-53 and Pro252 of Protein CASC4, Pro545 of Bromodomain-containing protein 2, Pro488 of Bromodomain-containing protein 3, Pro130 of Nucleolar RNA helicase 2, Pro51 of PDIA1, Pro395 of PDIA1, Pro404 of PDIA3, Pro89 of PDIA4, Pro204 of PDIA4 and Pro553 of PDIA4). The remaining sites could be either 4R-hydroxyproline or 3S-hydroxyproline. Recommendations are made to improve automated interpretation of proteomic data to enhance future proteomic research whose goal is to mine more of the remaining dark matter of the proteome.
               
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