Abstract
BackgroundTransmembrane proteins have important roles in cells, as they are involved in energy production, signal transduction, cell-cell interaction, cell-cell communication and more. In human cells, they are frequently targets for pharmaceuticals; therefore, knowledge about their properties and structure is crucial. Topology of transmembrane proteins provide a low resolution structural information, which can be a starting point for either laboratory experiments or modelling their 3D structures.ResultsHere, we present a database of the human α-helical transmembrane proteome, including the predicted and/or experimentally established topology of each transmembrane protein, together with the reliability of the prediction. In order to distinguish transmembrane proteins in the proteome as well as for topology prediction, we used a newly developed consensus method (CCTOP) that incorporates recent state of the art methods, with tested accuracies on a novel human benchmark protein set. CCTOP utilizes all available structure and topology data as well as bioinformatical evidences for topology prediction in a probabilistic framework provided by the hidden Markov model. This method shows the highest accuracy (98.5 % for discrinimating between transmembrane and non-transmembrane proteins and 84 % for per protein topology prediction) among the dozen tested topology prediction methods. Analysis of the human proteome with the CCTOP indicates that it contains 4998 (26 %) transmembrane proteins. Besides predicting topology, reliability of the predictions is estimated as well, and it is demonstrated that the per protein prediction accuracies of more than 60 % of the predictions are over 98 % on the benchmark sets and most probably on the predicted human transmembrane proteome too.ConclusionsHere, we present the most accurate prediction of the human transmembrane proteome together with the experimental topology data. These data, as well as various statistics about the human transmembrane proteins and their topologies can be downloaded from and can be visualized at the website of the human transmembrane proteome (http://htp.enzim.hu).ReviewersThis article was reviewed by Dr. Sandor Pongor, Dr. Michael Galperin and Dr. Pascale Gaudet (nominated by Dr Michael Galperin).Electronic supplementary materialThe online version of this article (doi:10.1186/s13062-015-0061-x) contains supplementary material, which is available to authorized users.
Highlights
Transmembrane proteins have important roles in cells, as they are involved in energy production, signal transduction, cell-cell interaction, cell-cell communication and more
The most reliable data can be found in the PDBTM database [1,2,3], which contains the 3D structure of transmembrane proteins (TMPs) together with the most likely membrane orientation determined by the TMDET algorithm [36]
Benchmark sets Most of the topography and topology prediction methods developed so far have been trained and/or tested on small benchmark sets, mostly on the so-called TMHMM 160 protein set [29], which contains three types of data: entries originated from the Möller data set; a prokaryote data set; and other individually collected proteins
Summary
Transmembrane proteins have important roles in cells, as they are involved in energy production, signal transduction, cell-cell interaction, cell-cell communication and more In human cells, they are frequently targets for pharmaceuticals; knowledge about their properties and structure is crucial. The biological functions of transmembrane proteins (TMPs) are widespread They are involved in diverse biological processes ranging from basic and primordial life functions such as energy production to the most advanced molecular functions of a multicellular organism, e.g. cell-cell communication or synaptic transmission. Despite these important roles, there are only about a hundred human TMPs with experimentally determined 3D structure [1,2,3]. The reported per protein transmembrane topology prediction accuracies of the various algorithms (see Additional file 1) were shown to be above 80 %, they
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