In this study, we investigate the extent to which techniques for homology modeling that were developed for water-soluble proteins are appropriate for membrane proteins as well. To this end we present an assessment of current strategies for homology modeling of membrane proteins and introduce a benchmark data set of homologous membrane protein structures, called HOMEP. First, we use HOMEP to reveal the relationship between sequence identity and structural similarity in membrane proteins. This analysis indicates that homology modeling is at least as applicable to membrane proteins as it is to water-soluble proteins and that acceptable models (with Cα-RMSD values to the native of 2 [Angstrom] or less in the transmembrane regions) may be obtained for template sequence identities of 30% or higher if an accurate alignment of the sequences is used. Second, we show that secondary-structure prediction algorithms that were developed for water-soluble proteins perform approximately as well for membrane proteins. Third, we provide a comparison of a set of commonly used sequence alignment algorithms as applied to membrane proteins. We find that high-accuracy alignments of membrane protein sequences can be obtained using state-of-the-art profile-to-profile methods that were developed for water-soluble proteins. Improvements are observed when weights derived from the secondary structure of the query and the template are used in the scoring of the alignment, a result which relies on the accuracy of the secondary-structure prediction of the query sequence. The most accurate alignments were obtained using template profiles constructed with the aid of structural alignments. In contrast, a simple sequence-to-sequence alignment algorithm, using a membrane protein-specific substitution matrix, shows no improvement in alignment accuracy. We suggest that profile-to-profile alignment methods should be adopted to maximize the accuracy of homology models of membrane proteins.Membrane proteins are believed to comprise 20-30% of the proteins in a genome (1-3) and represent a significant proportion of therapeutic drug targets (4). However, as a result of difficulties in experimental structure determination, they constitute only ~1% of the structures available in the protein data bank (PDB) (5). The absence of structural information severely limits our ability to understand membrane protein function. Based on previous experience with water-soluble proteins, it is likely that computational structure prediction will provide a useful approach to generating models for these proteins. Typically, the most accurate models of protein structures are achieved through homology modeling, where a known structure is used as a template for the construction of a model of a related protein (6). However, it remains unclear whether the methods and assumptions used in homology modeling of water-soluble proteins can be applied directly to membrane proteins without modification.