back to HMMSTR/Rosetta Prediction Server

The HMMSTR/Rosetta Server predicts the structure of proteins from the sequence : secondary, local, supersecondary, and tertiary.

    Secondary structure in the form of 3-states (H,E,L)
    Local structure in the form of backbone torsion angles (phi,psi)
    Supersecondary structure in the form of context symbols (for strands and beta turns)
    Teriary structure in the form of coordinates

Credits: Chris Bystroff , Vesteinn Thorsson , David Baker , Yu Shao

Please cite:
    Bystroff C & Shao Y. (2002). Fully automated ab initio protein structure prediction using I-SITES, HMMSTR and ROSETTA. Bioinformatics 18 Suppl 1, S54-61.
    Bystroff C, Thorsson V & Baker D. (2000). HMMSTR: A hidden markov model for local sequence-structure correlations in proteins. Journal of Molecular Biology 301, 173-90.

Other contributors:
Yu Shao, Kirsten Piotrowski, Lindsay Nelson, Georgi Shablovsky, Namdi MacFoy, Feng Gao, Patrick Buck, Yaoming Huang, Peter Watson.

HMMSTR is a hidden Markov model based on the I-sites Library of sequence-structure motifs.
Download HMMSTR and I-sites papers

Image of HMMSTR backbone angle-specific model: lambda-R

ROSETTA is a Monte Carlo Fragment Insertion protein folding program developed by Kim Simons, David Baker, Ingo Rudzinski and Charles Kooperberg (Simons et al, 1997). Please contact David Baker for more information.

This server also uses a hidden Markov model (HMMSTR) for local and secondary structure prediction, based on the I-sites Library. (JMB 301(1):173-190, 2000)
Read the paper online at Idealibrary.
Download the PDF-format preprint.

This server is experimental. Some of the methods used are untested and/or unpublished. Use the server and its results at your own risk. For more information, contact the authors.

If you need only fragment predictions, please dont check "set of 3D coordinates".


NOTE: You can UPLOAD or PASTE ANY FORMAT, including single sequences. (i.e. If you upload a file, the textbox will be ignored.) Please make sure your format is acceptable by looking at the examples.

TO USE PHD secondary structure predictions along with I-sites,
submit your sequence to the PredictProtein server to generate an alignment and predict SS. Ask for HSSP output. Then submit the returned HSSP file, with the SS prediction at the tail of it, to this server (either upload the file or paste it into the textbox.) Then check PHD + I-sites in the EXPERT section, and submit. An optimized combination of the two methods will be used.

Last updated: Wed Jul 30 07:58:57 EDT 2008