JPred4: a protein secondary structure prediction server

JPred4 (http://www.compbio.dundee.ac.uk/jpred4) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction. In addition to protein secondary structure, JPred also makes predictions of solvent accessibility and coiled-coil regions. The JPred service runs up to 94 000 jobs per month and has carried out over 1.5 million predictions in total for users in 179 countries. The JPred4 web server has been re-implemented in the Bootstrap framework and JavaScript to improve its design, usability and accessibility from mobile devices. JPred4 features higher accuracy, with a blind three-state (α-helix, β-strand and coil) secondary structure prediction accuracy of 82.0% while solvent accessibility prediction accuracy has been raised to 90% for residues <5% accessible. Reporting of results is enhanced both on the website and through the optional email summaries and batch submission results. Predictions are now presented in SVG format with options to view full multiple sequence alignments with and without gaps and insertions. Finally, the help-pages have been updated and tool-tips added as well as step-by-step tutorials.

[1]  Sameer Velankar,et al.  PDBe: Protein Data Bank in Europe , 2010, Nucleic Acids Res..

[2]  J. Garnier,et al.  Fold recognition using predicted secondary structure sequences and hidden Markov models of protein folds , 1997, Proteins.

[3]  Alessandro Vullo,et al.  Protein Structural Motif Prediction in Multidimensional ø-Psi Space Leads to Improved Secondary Structure Prediction , 2006, J. Comput. Biol..

[4]  Alberto Santamaría-Pang,et al.  Flexible fitting in 3D-EM guided by the structural variability of protein superfamilies. , 2006, Structure.

[5]  P. Bradley,et al.  Toward High-Resolution de Novo Structure Prediction for Small Proteins , 2005, Science.

[6]  M. Sternberg,et al.  Enhanced genome annotation using structural profiles in the program 3D-PSSM. , 2000, Journal of molecular biology.

[7]  Christopher Bystroff,et al.  Fully automated ab initio protein structure prediction using I-STES, HMMSTR and ROSETTA , 2002, ISMB.

[8]  G J Barton,et al.  Application of multiple sequence alignment profiles to improve protein secondary structure prediction , 2000, Proteins.

[9]  Aoife McLysaght,et al.  Porter: a new, accurate server for protein secondary structure prediction , 2005, Bioinform..

[10]  Thomas Earnest,et al.  Automation of X-ray crystallography , 2000, Nature Structural Biology.

[11]  Geoffrey J. Barton,et al.  Jalview Version 2—a multiple sequence alignment editor and analysis workbench , 2009, Bioinform..

[12]  Sameer Velankar,et al.  PDBe: Protein Data Bank in Europe , 2009, Nucleic Acids Res..

[13]  Richard M. Jackson,et al.  An evaluation of automated homology modelling methods at low target-template sequence similarity , 2007, Bioinform..

[14]  R. Srinivasan,et al.  Ab initio prediction of protein structure using LINUS , 2002, Proteins.

[15]  B. Rost,et al.  Protein fold recognition by prediction-based threading. , 1997, Journal of molecular biology.

[16]  Robert D. Finn,et al.  HMMER web server: interactive sequence similarity searching , 2011, Nucleic Acids Res..

[17]  Peter B. McGarvey,et al.  UniRef: comprehensive and non-redundant UniProt reference clusters , 2007, Bioinform..

[18]  Thomas A. Hopf,et al.  Protein 3D Structure Computed from Evolutionary Sequence Variation , 2011, PloS one.

[19]  Thomas A. Hopf,et al.  Three-Dimensional Structures of Membrane Proteins from Genomic Sequencing , 2012, Cell.

[20]  Christian Cole,et al.  The Jpred 3 secondary structure prediction server , 2008, Nucleic Acids Res..

[21]  Burkhard Rost,et al.  The PredictProtein server , 2003, Nucleic Acids Res..

[22]  A. Sali,et al.  Protein Structure Prediction and Structural Genomics , 2001, Science.

[23]  Liam J. McGuffin,et al.  Improvement of the GenTHREADER Method for Genomic Fold Recognition , 2003, Bioinform..

[24]  Yaoqi Zhou,et al.  Achieving 80% ten‐fold cross‐validated accuracy for secondary structure prediction by large‐scale training , 2006, Proteins.

[25]  Daniel W. A. Buchan,et al.  Protein annotation and modelling servers at University College London , 2010, Nucleic Acids Res..

[26]  Thomas Szyperski,et al.  Protein NMR spectroscopy in structural genomics , 2000, Nature Structural Biology.

[27]  G. Barton,et al.  The limits of protein secondary structure prediction accuracy from multiple sequence alignment. , 1993, Journal of molecular biology.

[28]  Steven E. Brenner,et al.  SCOPe: Structural Classification of Proteins—extended, integrating SCOP and ASTRAL data and classification of new structures , 2013, Nucleic Acids Res..

[29]  W. Kabsch,et al.  How good are predictions of protein secondary structure? , 1983, FEBS letters.

[30]  Avner Schlessinger,et al.  PredictProtein—an open resource for online prediction of protein structural and functional features , 2014, Nucleic Acids Res..

[31]  David T. Jones,et al.  Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction , 2007, BMC Bioinformatics.

[32]  María Martín,et al.  Activities at the Universal Protein Resource (UniProt) , 2013, Nucleic Acids Res..

[33]  John D. Westbrook,et al.  TargetDB: a target registration database for structural genomics projects , 2004, Bioinform..

[34]  P. Bradley,et al.  High-resolution structure prediction and the crystallographic phase problem , 2007, Nature.

[35]  A. Lesk,et al.  Assessment of novel fold targets in CASP4: Predictions of three‐dimensional structures, secondary structures, and interresidue contacts , 2001, Proteins.

[36]  Jonathan Casper,et al.  Combining local‐structure, fold‐recognition, and new fold methods for protein structure prediction , 2003, Proteins.