Golgi Predictor Description
A new method has been developed to predict Golgi membrane proteins based on their transmembrane domains.
To establish the prediction procedure, we took the hydrophobicity values and frequencies of different residues within the transmembrane domains into consideration.
A simple linear discriminant function was developed with a small number of parameters derived from a dataset of Type II transmembrane proteins of known localisation.
This can discriminate between proteins destined for the Golgi apparatus or other locations (post-Golgi) with a success rate of 91.5% or 96.5%, respectively,
on our redundancy-reduced data sets. Our method is consistent with the experimentally defined models for the retention of Golgi proteins that conclude
that the length of the transmembrane domains dictates the sorting of these proteins.
Strategy for the Prediction of Golgi Localised Type II Transmembrane Proteins.
- To date, the majority of single span membrane proteins within the Golgi complex are Type II (cytoplasmic N-terminus/lumenal C-terminus).
Therefore, this prediction method is only valid for Type II transmembrane proteins. Computational predictions of such proteins are often inaccurate
due primarily to false-positive predictions of N-terminal signal peptides as membrane anchors.
- Submission of your Type II transmembrane protein to our prediction method for analysis.
Output from the method is simply Protein_ID_XXXX is predicted to be Golgi localised or Protein_ID_XXXX is predicted to transit through the Golgi (post-Golgi localisation).
- Our approach predicts whether or not a membrane protein would stay within the Golgi or move beyond it to a post-Golgi compartment.
Therefore, for this prediction to be accurate the protein must reach the Golgi. As a result one source of false-positive results from this predictor will be
Type II membrane proteins that reside within other regions of the cell. This will include residents of the endoplasmic reticulum and the mitochondria.
Therefore, we strongly recommend that you also analyse you protein sequence for additional subcellular localisation signals.
For example, resident endoplasmic reticulum proteins will have a di-basic motif within their cytoplasmic domains
(R. D. Teasdale and M. R. Jackson, Ann. Rev. Cell Dev. Biol., 12, 27-54 (1996)).
These motifs can be predicted using PSORT II (http://psort.nibb.ac.jp/).
Yuan Z, Teasdale RD.
Prediction of Golgi type II membrane proteins based on their transmembrane domains.
Bioinformatics. 2002 Aug 18(8): 1109-15.