A large number of modular domains that exhibit specific lipid binding properties 
are present in many membrane proteins involved in trafficking and signal 
transduction. These domains are present in either eukaryotic peripheral membrane 
or transmembrane proteins and are responsible for the non-covalent interactions 
of these proteins with membrane lipids. Here we report a profile Hidden Markov 
Model based method capable of detecting Membrane Binding Proteins (MBPs) from 
information encoded in their amino acid sequence, called MBPpred. The method 
identifies MBPs that contain one or more of the Membrane Binding Domains (MBDs) 
that have been described to date, and further classifies these proteins based on 
their position in respect to the membrane, either as peripheral or 
transmembrane. MBPpred is available online at 
http://bioinformatics.biol.uoa.gr/MBPpred. This method was applied in selected 
eukaryotic proteomes, in order to examine the characteristics they exhibit in 
various eukaryotic kingdoms and phyla.