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Topology of a Transmembrane protein refers to the exact number and location of membrane spanning segments and their orientation relative to the membrane.〔(Membrane-protein topology ) by Gunnar von Heijne〕 Determining the atomic level level structure of transmembrane proteins is rather challenging due the experimental conditions, however in most cases their topology provides sufficient information. There are several computational methods for predicting alpha-helical transmembrane domains (i.e. topography). Pioneer methods utilizied the fact that membrane spanning regions contain more hydrophobic residues than other parts of the protein, however applying different hydrophobic scales altered the prediction results. Later several statistical method was developed to improve the topography prediction, as well as a special alignment method was introduced.〔(DAS )〕 According to the positive-inside rule,〔(The distribution of positively charged residues in bacterialinner membrane proteins correlates with the trans-membrane topology )〕 cytoslic loops near the the lipid bilayer contain more positively charged amino acids. Applying this information resulted in the first topology prediction methods. As more structures were determined machine learning algorithms appeared. Supervised learning methods are trained on a set of experminetally determined structures, however these methods highly depend on the training set used.〔(Predicting Transmembrane Protein Topology with a Hidden Markov Model: Application to Complete Genomes )〕〔(TMHMM server )〕〔(Phobius server )〕〔(OCTOPUS server )〕 Unsupervised learning methods are based on the principle that topology depends on the maximum divergence of the amino acid distributions in different structural parts.〔(Principles governing amino acid composition of integral membrane proteins: application to topology prediction )〕〔(HMMTOP server )〕 It was also shown, that locking a segment location based on prior knowledge about the structure improves the prediction accuracy.〔(The HMMTOP transmembrane topology prediction server )〕 This feature has been added to some of the existing prediction methods.〔(HMMTOP server )〕〔(Phobius server )〕 It is important to note that several methods are not able to distinguish Signal peptide-s at the N-terminus of the protein and transmembrane segments, or discriminate Transmembrane protein-s and Globular protein-s.〔(Topology Prediction of Helical Transmembrane Proteins: How Far HaveWe Reached? )〕 The most recent methods use consensus prediction (i.e. they use several algorithm to determined the final topology) 〔(TOPCONS server )〕 and automatically incorporate previously determined experimental informations.〔(CCTOP server )〕 It is also possible to predict beta-barrel membrane proteins' topology. There are a few databases which provide topologies of membrane proteins: Uniprot is the most comprehensive protein database, the recently updated TOPDB〔(TOPDB: topology data bank of transmembrane proteins )〕〔(Expediting topology data gathering for the TOPDB database )〕〔(TOPDB database )〕 and ExTopoDB〔(ExTopoDB: a database of experimentally derived topological models of transmembrane proteins )〕〔(ExTopoDB )〕 contains experimentally determined localizations, TOPDOM is a database of domains located conservatively in one side of transmembrane proteins,〔(TOPDOM database )〕 the HTP database〔(The human transmembrane proteome )〕〔(The human transmembrane proteome database )〕 is the collection of human transmembrane proteins. ==References== 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Membrane topology」の詳細全文を読む スポンサード リンク
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