Prediction of lipid posttranslational modifications and localization signals from protein sequences: big-Pi, NMT and PTS1

Abstract

Many posttranslational modifications (N-myristoylation or glycosylphosphatidylinositol (GPI) lipid anchoring) and localization signals (the peroxisomal targeting signal PTS1) are encoded in short, partly compositionally biased regions at the N- or C-terminus of the protein sequence. These sequence signals are not well defined in terms of amino acid type preferences but they have significant interpositional correlations. Although the number of verified protein examples is small, the quantification of several physical conditions necessary for productive protein binding with the enzyme complexes executing the respective transformations can lead to predictors that recognize the signals from the amino acid sequence of queries alone. Taxon-specific prediction functions are required due to the divergent evolution of the active complexes. The big-Pi tool for the prediction of the C-terminal signal for GPI lipid anchor attachment is available for metazoan, protozoan and plant sequences. The myristoyl transferase (NMT) predictor recognizes glycine N-myristoylation sites (at the N-terminus and for fragments after processing) of higher eukaryotes (including their viruses) and fungi. The PTS1 signal predictor finds proteins with a C-terminus appropriate for peroxisomal import (for metazoa and fungi). Guidelines for application of the three WWW-based predictors (http://mendel.imp.univie.ac.at/) and for the interpretation of their output are described.

Figure 1

Example output of the NMT predictor. The information generated upon sequence submission is similarly structured for all three servers. As example, the server output is presented for the yeast 26 S protease regulatory subunit 4 homologue (RPT2, SWISS-PROT accession P40327). For control purposes, the complete sequence is returned first with the examined motif highlighted. After the general classification of the prediction (reliable, twilight zone, not predicted) and the overall score and probability of false positive prediction, the components of the score function are listed. In this case, no deviation for the physical property pattern was measured although the protein is not part of the learning set. N-myristoylation of the RPT2 protein has been predicted (9) and the experimental verification reported (15).