Membrane topology

[12][13][14][15] Unsupervised learning methods are based on the principle that topology depends on the maximum divergence of the amino acid distributions in different structural parts.

[16][17] It was also shown that locking a segment location based on prior knowledge about the structure improves the prediction accuracy.

[20] HTP database[21][22] provides a collection of topologies that are computationally predicted for human transmembrane proteins.

Discrimination of signal peptides and transmembrane segments is an additional problem in topology prediction treated with a limited success by different methods.

By predicting signal peptides and transmembrane helices simultaneously (Phobius[14]), the errors caused by cross-prediction are reduced and the performance is substantially increased.

Group I and II transmembrane proteins have opposite final topologies. Group I proteins have the N terminus on the far side and C terminus on the cytosolic side. Group II proteins have the C terminus on the far side and N terminus in the cytosol. However final topology is not the only criterion for defining transmembrane protein groups, rather location of topogenic determinants and mechanism of assembly is considered in the classification [ 2 ]