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OPM: orientations of proteins in membranes
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Andrei L.Lomize
, Irina D.Pogozheva
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Thousands of membrane-associated proteins are currently deposited in the Protein Data Bank (PDB) , and their number is rapidly growing in part due to the Structural Genomics Initiative. However, the precise spatial positions of these proteins in membranes are unknown. To fill this gap, we have recently developed a fast computational approach for calculating the orientations of membrane proteins in lipid bilayers using experimental 3D structures as input. The approach is based on the concept that biological membranes are fluid and highly flexible, and therefore, may be described by an implicit solvation model. This approach demonstrates an excellent agreement with experimental studies of 24 transmembrane (TM) proteins by mutagenesis, chemical modification, spin-labeling, fluorescence quenching, NMR and other techniques. Moreover, this method correctly defines the attachment site and membrane penetration depths of numerous monotopic/peripheral proteins with solvent-exposed hydrophobic spots.
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The results have been deposited in our Orientations of Proteins in Membranes (OPM) database, a unique bioinformatics resource designed to organize available structural information about TM and monotopic/peripheral membrane proteins, and provide a useful tool for the analysis, sorting and searching of membrane proteins based on their structure, evolutionarily classification, topology, localization, and calculated orientational parameters.
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Currently we plan to improve our method and significantly expand the OPM database in order to include all TM, integral monotopic and most peripheral proteins and membrane-active peptides from the PDB.
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Improvements of the method will include: (a) development of an automated procedure for conformational adjustments of flexible side-chains at the membrane interface, which is necessary for large-scale analysis of PDB structures; (b) incorporation of scoring functions describing the interactions of polar, aromatic and basic residues with lipid head groups, which is based on statistical distributions of different atom types along the membrane normal in TM proteins from different membranes. The improved method will be publicly available through a web server.
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