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

Guy Yachdav, Edda Kloppmann, Laszlo Kajan, Maximilian Hecht, Tatyana Goldberg, Tobias Hamp, Peter Hönigschmid, Andrea Schafferhans, Manfred Roos, Michael Bernhofer, Lothar Richter, Haim Ashkenazy, Marco Punta, Avner Schlessinger, Yana Bromberg, Reinhard Schneider, Gerrit Vriend, Chris Sander, Nir Ben-Tal, Burkhard Rost

Research output: Contribution to journalArticlepeer-review

446 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)W337-W343
JournalNucleic Acids Research
Volume42
Issue numberW1
DOIs
StatePublished - 1 Jul 2014
Externally publishedYes

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