PredictProtein--an open resource for online prediction of protein structural and functional features

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembra...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nucleic acids research 2014-07, Vol.42 (Web Server issue), p.W337-W343
Hauptverfasser: Yachdav, Guy, Kloppmann, Edda, Kajan, Laszlo, Hecht, Maximilian, Goldberg, Tatyana, Hamp, Tobias, Hönigschmid, Peter, Schafferhans, Andrea, Roos, Manfred, Bernhofer, Michael, Richter, Lothar, Ashkenazy, Haim, Punta, Marco, Schlessinger, Avner, Bromberg, Yana, Schneider, Reinhard, Vriend, Gerrit, Sander, Chris, Ben-Tal, Nir, Rost, Burkhard
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein-protein binding sites (ISIS2), protein-polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org.
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gku366