Search results
Results from the WOW.Com Content Network
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.
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 ...
The Phyre and Phyre2 servers predict the three-dimensional structure of a protein sequence using the principles and techniques of homology modeling.Because the structure of a protein is more conserved in evolution than its amino acid sequence, a protein sequence of interest (the target) can be modeled with reasonable accuracy on a very distantly related sequence of known structure (the ...
Hirokawa, Boon-Chieng, Mitaku, SOSUI: Classification and secondary structure prediction for membrane proteins, Bioinformatics Vol.14 S.378-379 (1998) ^ Masami Ikeda, Masafumi Arai, Toshio Shimizu, Evaluation of transmembrane topology prediction methods by using an experimentally characterized topology dataset, Genome Informatics 11: 426–427 (2000) ^
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.
List of notable protein secondary structure prediction programs. Name Method description Type Link Initial release RaptorX-SS8
Approaches include homology modeling, protein threading, ab initio methods, secondary structure prediction, and transmembrane helix and signal peptide prediction. In particular, deep learning based on long short-term memory has been used for this purpose since 2007, when it was successfully applied to protein homology detection [ 59 ] and to ...
For genomes with high GC content (>60%), Glimmer may generate a high number of false positive predictions and therefore should be used with caution. HMMER 2.3.2: Used for local Pfam Searches Homodeller 2.0: Locally developed homology modelling program. SignalP 3.0: Signal peptide prediction. TMHMM 2.0: Prediction of transmembrane helices in ...