Skip to main navigation Skip to search Skip to main content

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
  • Technical University of Munich
  • Biosof LLC
  • Columbia University
  • Tel Aviv University
  • Wellcome Sanger Institute
  • European Molecular Biology Laboratory
  • Mount Sinai School of Medicine
  • Rutgers University–New Brunswick
  • University of Luxembourg
  • Amalia Children's Hospital
  • Weill Cornell Medical College

Research output: Contribution to journalArticlepeer-review

516 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

Fingerprint

Dive into the research topics of 'PredictProtein - An open resource for online prediction of protein structural and functional features'. Together they form a unique fingerprint.

Cite this