Jpred Explained

Jpred v.4 is the latest version of the JPred Protein Secondary Structure Prediction Server^[1] which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction,^[2] that has existed since 1998 in different versions.^[3]

In addition to protein secondary structure, JPred also makes predictions of solvent accessibility and coiled-coil regions. The JPred service runs up to 134 000 jobs per month and has carried out over 2 million predictions in total for users in 179 countries.^[4]

JPred 2

The static HTML pages of JPred 2 are still available for reference.^[5]

JPred 3

The JPred v3^[6] followed on from previous versions of JPred developed and maintained by James Cuff and Jonathan Barber (see JPred References^[7]). This release added new functionality and fixed many bugs. The highlights are:

• New, friendlier user interface
• Retrained and optimised version of Jnet (v2) - mean secondary structure prediction accuracy of >81%
• Batch submission of jobs
• Better error checking of input sequences/alignments
• Predictions now (optionally) returned via e-mail
• Users may provide their own query names for each submission
• JPred now makes a prediction even when there are no PSI-BLAST hits to the query
• PS/PDF output now incorporates all the predictions

JPred 4

The current version of JPred (v4) has the following improvements and updates incorporated:

• Retrained on the latest UniRef90 and SCOPe/ASTRAL version of Jnet (v2.3.1) - mean secondary structure prediction accuracy of >82%.^[2]
• Upgraded the Web Server to the latest technologies (Bootstrap framework, JavaScript) and updating the web pages – improving the design and usability through implementing responsive technologies.
• Added RESTful API and mass-submission and results retrieval scripts - resulting in peak throughput above 20,000 predictions per day.^[8]
• Added prediction jobs monitoring tools.^[9]
• Upgraded the results reporting – both, on the web-site, and through the optional email summary reports: improved batch submission, added results summary preview through Jalview results visualization summary in SVG and adding full multiple sequence alignments into the reports.
• Improved help-pages, incorporating tool-tips, and adding one-page step-by-step tutorials.^[10]

Sequence residues are categorised or assigned to one of the secondary structure elements, such as alpha-helix, beta-sheet and coiled-coil.

Jnet uses two neural networks for its prediction. The first network is fed with a window of 17 residues over each amino acid in the alignment plus a conservation number. It uses a hidden layer of nine nodes and has three output nodes, one for each secondary structure element.The second network is fed with a window of 19 residues (the result of first network) plus the conservation number. It has a hidden layer with nine nodes and has three output nodes.^[11]

See also

• PSIPRED
• List of protein structure prediction software

Notes and References

1. Web site: JPred4: A Protein Secondary Structure Prediction Server. 16 July 2015.
2. Drozdetskiy. Alexey. Cole. Chris. Procter. James. Barton. Geoffrey. JPred4: a protein secondary structure prediction server. Nucleic Acids Research. Apr 16, 2015. 10.1093/nar/gkv332. 43. W1. W389–W394. 25883141. 4489285.
3. News: JPred old news . Oct 25, 1998 . 16 Jul 2015.
4. Web site: JPred4 statistics. 16 July 2015.
5. Web site: JPred2: legacy. 16 July 2015.
6. Web site: JPred3: previous version of JPred. 16 July 2015.
7. Web site: JPred4 references. 16 July 2015.
8. Web site: JPred4 RESTful API. 16 July 2015.
9. Web site: JPred4 monitoring tools. 16 July 2015.
10. Web site: JPred4 Help and Tutorials. 16 July 2015.
11. 10861942 . 40 . Application of multiple sequence alignment profiles to improve protein secondary structure prediction . August 2000 . Proteins . 502–11 . Cuff . JA . Barton . GJ . 3 . 10.1002/1097-0134(20000815)40:3<502::aid-prot170>3.0.co;2-q. 855816 .