Hydrophobic organization of alpha-helix membrane bundle in bacteriorhodopsin

RECOGNITION OF TRANSMEMBRANE SEGMENTS IN PROTEINS: REVIEW AND CONSISTENCY-BASED BENCHMARKING OF INTERNET SERVERS

Membrane proteins perform a number of crucial functions as transporters, receptors, and components of enzyme complexes. Identification of membrane proteins and prediction of their topology is thus an important part of genome annotation. We present here an overview of transmembrane segments in protein sequences, summarize data from large-scale genome studies, and report results of benchmarking of several popular internet servers.

[Prediction of the spatial structure of proteins: emphasis on membrane targets]

Knowledge of the spatial structure of proteins is a prerequisite for both awareness of their functional mechanisms and the framework for rational drug discovery and design. Meanwhile, direct structural determination is often hampered or impractical due to the complexity, expensiveness, and limited capabilities of experimental techniques. These issues are especially pronounced for integral membrane proteins. On numerous occasions, the theoretical prediction of protein structures may facilitate the process by exploiting physical or empirical principles. This paper surveys modern techniques for the prediction of the spatial structure of proteins using computer algorithms, and the main emphasis is placed on the most "complex" targets - membrane proteins (MPs). The first part of the review describes de novo methods based on empirical physical principles; in the second part, a comparative modeling philosophy, which accounts for the structure of related proteins, is described. Special focus is made regarding pharmacologically relevant classes of G-coupled receptors, receptor tyrosine ki-nases, and other MPs. Algorithms for the assessment of the models quality and potential fields of application of computer models are discussed.

Method To Assess Packing Quality of Transmembrane α-Helices in Proteins. 1. Parametrization Using Structural Data

Integral membrane proteins (MPs) are pharmaceutical targets of exceptional importance. Modern methods of three-dimensional protein structure determination often fail to supply the fast growing field of structure-based drug design with the requested MPs' structures. That is why computational modeling techniques gain a special importance for these objects. Among the principal difficulties limiting application of these methods is the low quality of the MPs' models built in silico. In this series of two papers we present a computational approach to the assessment of the packing "quality" of transmembrane (TM) alpha-helical domains in proteins. The method is based on the concept of protein environment classes, whereby each amino acid residue is described in terms of its environment polarity and accessibility to the membrane. In the first paper we analyze a nonredundant set of 26 TM alpha-helical domains and compute the residues' propensities to five predefined classes of membrane-protein environments. Here we evaluate the proposed approach only by various test sets, cross-validation protocols and ability of the method to delimit the crystal structure of visual rhodopsin, and a number of its erroneous theoretical models. More advanced validation of the method is given in the second article of this series. We assume that the developed "membrane score" method will be helpful in optimizing computer models of TM domains of MPs, especially G-protein coupled receptors.

A novel method for packing quality assessment of transmembrane alpha-helical domains in proteins

Here we present a novel method for assessment of packing quality for transmembrane (TM) domains of alpha-helical membrane proteins (MPs), based on analysis of available high-resolution experimental structures of MPs. The presented concept of protein-membrane environment classes permits quantitative description of packing characteristics in terms of membrane accessibility and polarity of the nearest protein groups. We demonstrate that the method allows identification of native-like conformations among the large set of theoretical MP models. The developed "membrane scoring function" will be of use for optimization of TM domain packing in theoretical models of MPs, first of all G-protein coupled receptors.

Differences in Binding Sites of Two Melatonin Receptors Help to Explain Their Selectivity to Some Melatonin Analogs: A Molecular Modeling Study

Numerous diseases have been linked to the malfunction of G-protein coupled receptors (GPCRs). Their adequate treatment requires rational design of new high-affinity and high-selectivity drugs targeting these receptors. In this work, we report three-dimensional models of the human MT(1) and MT(2) melatonin receptors, members of the GPCR family. The models are based on the X-ray structure of bovine rhodopsin. The computational approach employs an original procedure for optimization of receptor-ligand structures. It includes rotation of one of the transmembrane alpha-helices around its axis with simultaneous assessment of quality of the resulting complexes according to a number of criteria we have developed for this purpose. The optimal geometry of the receptor-ligand binding is selected based on the analysis of complementarity of hydrophobic/hydrophilic properties between the ligand and its protein environment in the binding site. The elaborated "optimized" models are employed to explore the details of protein-ligand interactions for melatonin and a number of its analogs with known affinity to MT(1) and MT(2) receptors. The models permit rationalization of experimental data, including those that were not used in model building. The perspectives opened by the constructed models and by the optimization procedure in the design of new drugs are discussed.