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This list of protein subcellular localisation prediction tools includes software, databases, and web services that are used for protein subcellular localization prediction. Some tools are included that are commonly used to infer location through predicted structural properties, such as signal peptide or transmembrane helices , and these tools ...
Constituent amino-acids can be analyzed to predict secondary, tertiary and quaternary protein structure. This list of protein structure prediction software summarizes notable used software tools in protein structure prediction, including homology modeling, protein threading, ab initio methods, secondary structure prediction, and transmembrane helix and signal peptide prediction.
A step called domain parsing, or domain boundary prediction, is usually done first to split a protein into potential structural domains. As with the rest of tertiary structure prediction, this can be done comparatively from known structures [ 32 ] or ab initio with the sequence only (usually by machine learning , assisted by covariation). [ 33 ]
These scales are commonly used to predict the transmembrane alpha-helices of membrane proteins. When consecutively measuring amino acids of a protein, changes in value indicate attraction of specific protein regions towards the hydrophobic region inside lipid bilayer .
The database provides information about the individual proteins including computationally generated three-dimensional models of their transmembrane alpha-helices spatially arranged in the membrane, topology, intracellular localizations, amino acid sequences, domain architecture, functional annotation and available experimental structures from ...
A transmembrane domain (TMD) is a membrane-spanning protein domain.TMDs may consist of one or several alpha-helices or a transmembrane beta barrel.Because the interior of the lipid bilayer is hydrophobic, the amino acid residues in TMDs are often hydrophobic, although proteins such as membrane pumps and ion channels can contain polar residues.
This causes the cross-prediction between them, which is a weakness of many transmembrane topology predictors. By predicting signal peptides and transmembrane helices simultaneously (Phobius [14]), the errors caused by cross-prediction are reduced and the performance is substantially increased. Another feature used to increase the accuracy of ...
Computational methods exploit the sequence signatures of disorder to predict whether a protein is disordered, given its amino acid sequence. The table below, which was originally adapted from [1] and has been recently updated, shows the main features of software for disorder prediction. Note that different software use different definitions of ...