Several lines of biochemical and pharmacological evidence have suggested that some G-protein-coupled receptors (GPCRs) form homo oligomers, hetero oligomers or both. The GPCRs oligomerizations are considered to be related to signal transduction and some diseases. Therefore, an accurate prediction of the residues that interact upon oligomerization interface would further our understanding of signal transduction and the diseases in which GPCRs are involved. One of the complications for such a prediction is that the interfaces differ with the subtypes, even within the same GPCR family. Focusing on the distribution of residues conserved on the molecular surface in a particular subtype, we developed a new method to predict the interface for the GPCR oligomers, and applied it to several subtypes of known GPCRs to check the sensitivity. Subsequently, we found that predicted interfaces of rhodopsin, D(2) dopamine receptor and beta(2) adrenergic receptor agreed with the experimentally suggested interfaces, despite difference in the interface region among the three subtypes. Moreover, a highly conserved residue detected from the D(2) dopamine receptor corresponded to a residue involved in a missense change found in the large family of myoclonus dystonia. Our observation suggests the possibility that the disease is caused by the disorder of the oligomerization, although the molecular mechanism of the disease has not been revealed yet. The benefits and the pitfalls of the new method will be discussed, based on the results of the applications.

Chemokine receptors (CKRs) function in the inflammatory response and in vertebrate homeostasis. Decoy and viral receptors are two types of CKR homologs with modified functions from those of the typical CKRs. The decoy receptors are able to bind ligands without signaling. On the other hand, the viral receptors show constitutive signaling without ligands. We examined the sites related to the functional difference. At first, the decoy and viral receptors were each classified into five groups, based on the molecular phylogenetic analysis. A multiple amino acid sequence alignment between each group and the CKRs was then constructed. The difference in the amino acid composition between the group and the CKRs was evaluated as the Kullback–Leibler (KL) information value at each alignment site. The KL information value is considered to reflect the difference in the functional constraints at the site. The sites with the top 5% of KL information values were selected and mapped on the structure of a CKR. The comparisons with decoy receptor groups revealed that the detected sites were biased on the intracellular side. In contrast, the sites detected from the comparisons with viral receptor groups were found on both the extracellular and intracellular sides. More sites were found in the ligand binding pocket in the analyses of the viral receptor groups, as compared to the decoy receptor groups. Some of the detected sites were located in the GPCR motifs. For example, the DRY motif of the decoy receptors was often degraded, although the motif of the viral receptors was basically conserved. The observations for the viral receptor groups suggested that the constraints in the pocket region are loose and that the sites on the intracellular side are different from those for the decoy receptors, which may be related to the constitutive signaling activity of the viral receptors.

BackgroundThe detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions.ResultsWe have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods.ConclusionsAppropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems.