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Background: We introduce a computational protocol for effective predictions of the supramolecular organization of integral transmembrane proteins, starting from the monomer. Despite the demonstrated constitutive and functional importance of supramolecular assemblies of transmembrane subunits or proteins, effective tools for structure predictions of such assemblies are still lacking. Our computational approach consists in rigid-body docking samplings, starting from the docking of two identical copies of a given monomer. Each docking run is followed by membrane topology filtering and cluster analysis. Prediction of the native oligomer is therefore accomplished by a number of progressive growing steps, each made of one docking run, filtering and cluster analysis. With this approach, knowledge about the oligomerization status of the protein is required neither for improving sampling nor for the filtering step. Furthermore, there are no size-limitations in the systems under study, which are not limited to the transmembrane domains but include also the water-soluble portions.

A computational approach based upon rigid-body docking, ad hoc filtering, and cluster analysis has been combined with a protocol for dimerization free energy estimations to predict likely interfaces in the neurotensin 1 receptor (NTS1) homodimers. The results of this study suggest that the likely intermonomer interfaces compatible with in vitro binding affinity constants essentially involve helices 1, 2, and 4 and do not include disulfide bridges. The correlative model initially developed on Glycophorin A and herein extended to a G protein-Coupled Receptor (GPCR) appears to be a useful tool for estimating the association free energies of transmembrane proteins independent of the size and shape of the interface. In the desirable future cases, in which in vitro intermonomer binding affinities will be available for other GPCRs, such a correlative model will work as an additional criterion for helping in the selection of the most likely dimers.

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