Topology Prediction of Membrane Proteins: Why, How and When?
Membrane proteins are of broad interest since they constitute a large fraction of the proteome in all organisms, up to 20-30%. They play a crucial role in many cellular processes mediating information flow and molecular transport across otherwise nearly impermeable membranes. Traditional three-dimensional structural analyses of membrane proteins are difficult to perform, which makes studies of other structural aspects important. The topology of an ?-helical membrane protein is a two-dimensional description of how the protein is embedded in the membrane and gives valuable information on both structure and function.This thesis is focused on predicting the topology of ?-helical membrane proteins and on assessing and improving the prediction accuracy. Reliability scores have been derived for a number of prediction methods, and have been integrated into the widely used TMHMM predictor. The reliability score makes it possible to estimate the trustworthiness of a prediction.Mapping the full topology of a membrane protein experimentally is time-consuming and cannot be done on a genome-wide scale. However, determination of the location of one part of a membrane protein relative to the membrane is feasible. We have analyzed the impact of incorporating such experimental information a priori into TMHMM predictions and show that the accuracy increases significantly. We further show that the C-terminal location of a membrane protein (inside or outside) is the optimal information to use as a constraint in the predictions.By combining experimental techniques for determining the C-terminal location of membrane proteins with topology predictions, we have produced reliable topology models for the majority of all membrane proteins in the model organisms E. coli and S. cerevisiae. The results were further expanded to ~15,000 homologous proteins in 38 fully sequenced eukaryotic genomes. This large set of reliable topology models should be useful, in particular as the structural data for eukaryotic membrane proteins is very limited.
Source Type:Doctoral Dissertation
Keywords:NATURAL SCIENCES; Chemistry; Theoretical chemistry; membrane protein; topology prediction; bioinformatics; biokemi; Biochemistry
Date of Publication:01/01/2007