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Few sequence alignment methods have been designed specifically for integral membrane proteins, even though these important proteins have distinct evolutionary and structural properties that might affect their alignments. Existing approaches typically consider membrane-related information either by using membrane-specific substitution matrices or by assigning distinct penalties for gap creation in transmembrane and non-transmembrane regions. Here, we ask whether favoring matching of predicted transmembrane segments within a standard dynamic programming algorithm can improve the accuracy of pairwise membrane protein sequence alignments. We tested various strategies using a specifically designed program called AlignMe. An updated set of homologous membrane protein structures, called HOMEP2, was used as a reference for optimizing the gap penalties. The best of the membrane-protein optimized approaches were then tested on an independent reference set of membrane protein sequence alignments from the BAliBASE collection. When secondary structure (S) matching was combined with evolutionary information (using a position-specific substitution matrix (P)), in an approach we called AlignMePS, the resultant pairwise alignments were typically among the most accurate over a broad range of sequence similarities when compared to available methods. Matching transmembrane predictions (T), in addition to evolutionary information, and secondary-structure predictions, in an approach called AlignMePST, generally reduces the accuracy of the alignments of closely-related proteins in the BAliBASE set relative to AlignMePS, but may be useful in cases of extremely distantly related proteins for which sequence information is less informative. The open source AlignMe code is available at https://sourceforge.net/projects/alignme/, and at http://www.forrestlab.org, along with an online server and the HOMEP2 data set.
Transmembrane proteins play crucial roles in biological systems as active or passive channels and receptors. Experimentally only few structures could be determined so far. Gaining structural insights enables besides a general understanding of biological mechanisms also further processing such as in drug design. Due to the lack of experimental data, reliable theoretical predictions would be of high value. However, for the same reason, missing data, the knowledge-based class of prediction methods that is well established for soluble proteins can not be applied. The goal of predicting transmembrane protein structures with ab initio methods demands locating the free energy minimum. Main difficulties here are, first, the computational costs of explicitly calculating all involved interactions and, second, providing an algorithm that is capable of finding the minimum within an extremely complex and rugged energy landscape. We have developed promising energy functions that describe the interactions of amino acids on a residue level, reducing computational costs while still containing most information on the atomistic level. We have also found a way to describe the interaction of the residues with its surrounding in a realistic manner by distinguishing residues exposed to the environment from those buried within helices using a sphere algorithm. The sphere algorithm can also be applied for a different purpose: one can measure how densely sidechains are packed for certain helical conformations, and thereby get an estimate of the sidechain entropy. In addition, overcrowding effects can be identified which are not well-described by the energy functions due to the pairwise calculation. To determine the absolute free energy minimum, we assume the helices to be located on an equidistance grid with slightly larger distances than to be expected. Optimizing the helices on the grid provides a starting point that should enable common minimizing algorithms, gradient-based or not, to find the absolute minimum beyond the grid. To simulate the dynamics of the helices on large time scales, we split them into rigid body dynamics and internal dynamics in terms of the dihedrals. The former one is well-known with its inherent problem of numerical drift and plenty of approaches to it, among which we have chosen the quaternions to represent the rotation of the rigid bodies. The latter one requires a detailed analysis of the torque size exerted on the dihedrals caused by the forces acting on the residues.