Open Access

Marcus Stamm

• Membrane proteins are biological macromolecules that are located in a cell’s membrane and are responsible for essential functions within an organism, which makes them to prominent drug targets. The extraction of membrane proteins from the hydrophobic membrane bilayer to determine high-resolution crystal structures is a difficult task and only 2% of all solved proteins structures are membrane proteins. Computational methods may help to gain deeper insights into membrane protein structures and their functions. This study will give an overview of such computational methods on a representative set of membrane proteins and will provide ideas for future computational and experimental research on membrane proteins. In a first step (chapter 2), I updated an earlier, manually-curated data set of homologous membrane proteins (HOMEP) to more recent versions in 2010 (HOMEP2) and 2013 (HOMEP3) using an automated clustering approach. High-resolution structures of membrane proteins listed in the PDB_TM database were structurally aligned and subsequently clustered using structural similarity scores. Both data sets were used as a standard gold reference set for subsequent work. Subsequently, I have updated and applied the sequence alignment program AlignMe to determine protein descriptors that are suitable for detecting evolutionary relationship between homologous a-helical membrane proteins. Single input descriptors were tested alone and in combination with each other in different modes of AlignMe by optimizing gap penalties on the HOMEP2 data set. Most accurate alignments and homology models on the HOMEP2 data set were observed when using position-specific substitution information (P), secondary structure propensities (S) and transmembrane propensities (T) in the AlignMe PST mode. An evaluation on an independent reference set of membrane protein sequence alignments from the BAliBASE collection showed that different modes of AlignMe are suitable for different sequence similarity levels. The AlignMe PST mode improved the alignment accuracy significantly for distantly related proteins, whereas for closely-related proteins from the BAliBASE set the AlignMe PS mode was more suitable. This work was published in March 2013 in PLOS ONE. In order to allow also an easier usage of the AlignMe program, I have implemented a web server of AlignMe (chapter 4) that provides the optimized settings and gap penalties for the AlignMe P, PS and PST modes. A comparison to other recent alignment web server shows that the alignments of AlignMe are similar or even more accurate than those of other methods, especially for very distantly related proteins for which the inclusion of membrane protein information has been shown to be suitable. This work was published in the NAR web server issue in July 2014. Although membrane-specific information has been shown to be suitable for aligning distantly related membrane proteins on a sequence level, such information was not incorporated into structural alignment programs making it unclear which method is the most suitable for aligning membrane proteins. Thus, I compared 13 widely-used pairwise structural alignment methods on an updated reference set of homologous membrane protein structures (HOMEP3) and evaluated their accuracy by building models based on the underlying sequence alignments and used scoring functions (e.g., AL4 or CAD-score) to rate the model accuracy (chapter 5). The analysis showed that fragment-based approaches such as FR-TM-align are the most useful for aligning structures of membrane proteins that have undergone large conformational changes whereas rigid approaches were more suitable for proteins that were solved in the same or a similar state. However, no method showed a significant higher accuracy than any other. Additionally, all methods lack a measure to rate the reliability of the accuracy for a specific position within a structure alignment. In order to solve these problems, I propose a consensus-type approach that combines alignments from four different methods, namely FR-TM-align, DaliLite, MATT and FATCAT and assigns a confidence value to each position of the alignment that describes the agreement between the methods. This work has been published 2015 in the journal “PROTEINS: structure, function and bioinformatics”. Consensus alignments were then generated for each pair of proteins of the HOMEP3 data set and subsequently analyzed for single evolutionary events within membrane spanning segments and for irregular structures (e.g., 310- and p-helices) (chapter 6). Interestingly, single insertions and deletions could be observed with the help of consensus alignments in the conserved membrane-spanning segments of membrane proteins in four protein families. The detection of such single InDels might help to identify crucial residues for a proteins function.