Transmembrane helix detection software tools | Membrane protein data analysis
In eukaryotes, all known membrane proteins in the plasma membrane consist of alpha helical transmembrane (TM) bundles connected by loops. Accurate computational prediction of transmembrane helical segments is important for modeling membrane protein 3D structure and function.
Makes a prediction of membrane-spanning regions and their orientation. The algorithm is based on the statistical analysis of TMbase, a database of naturally occurring transmembrane proteins. The prediction is made using a combination of several weight-matrices for scoring.
Predicts all membrane proteins in a large collection of mostly fully sequenced genomes, and provides statistics on the frequency of proteins with different topologies. One of the main advantages of an Hidden Markov Model (HMM) is that it is possible to model helix length, which has only been done fairly crudely in most other methods, by setting upper and lower limits for the length of a membrane helix.
Predicts the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms: Gram-positive prokaryotes, Gram-negative prokaryotes, and eukaryotes. SignalP is a neural network–based method which can discriminate signal peptides from transmembrane regions. The software incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks.
Combines transmembrane topology and signal peptide predictions. Phobius provides an easy and accurate mean to predict signal peptides and transmembrane topology from an amino acid sequence. Phobius makes an optimal choice between transmembrane segments and signal peptides, and also allows constrained and homology-enriched predictions.
Predicts both the localization of helical transmembrane segments and the topology of transmembrane proteins. The user is allowed to submit additional information about segment localization to enhance the prediction power. This option improves the prediction accuracy as well as helps the interpretation of experimental results, i.e. in epitope insertion experiments.
Constructs a system for predicting membrane proteins by an index of amino acids. Amphiphilicity plots of membrane proteins of known 3D structure indicat that this kind of plot is useful in finding the end region of transmembrane helices. The accuracy of the classification of proteins was 99% and the corresponding value for the transmembrane helix prediction was 97%.
A web server that performs automated, in-depth annotation of bacterial genomic (chromosomal and plasmid) sequences. BASys uses more than 30 programs to determine nearly 60 annotation subfields for each gene, including gene/protein name, GO function, COG function, possible paralogues and orthologues, molecular weight, isoelectric point, operon structure, subcellular localization, signal peptides, transmembrane regions, reactions, and pathways. The textual annotations and images that are provided by BASys can be generated in approximately 16 hours for an average bacterial chromosome (5 Megabases. 5000 genes), or approximately 350 coding regions per hour.