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Bioinformatics Vol. 18 no. 90001 2002
Pages S54-S61
© 2002 Oxford University Press

Fully automated ab initio protein structure prediction using I-SITES, HMMSTR and ROSETTA

Christopher Bystroff * and Yu Shao

Department of Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, USA

Received on January 24, 2002 ; revised on March 27, 2002 ; accepted on March 27, 2002

Motivation: The Monte Carlo fragment insertion method for protein tertiary structure prediction (ROSETTA) of Baker and others, has been merged with the I-SITES library of sequence structure motifs and the HMMSTR model for local structure in proteins, to form a new public server for the ab initio prediction of protein structure. The server performs several tasks in addition to tertiary structure prediction, including a database search, amino acid profile generation, fragment structure prediction, and backbone angle and secondary structure prediction. Meeting reasonable service goals required improvements in the efficiency, in particular for the ROSETTA algorithm.

Results: The new server was used for blind predictions of 40 protein sequences as part of the CASP4 blind structure prediction experiment. The results for 31 of those predictions are presented here. 61% of the residues overall were found in topologically correct predictions, which are defined as fragments of 30 residues or more with a root-mean-square deviation in superimposed alpha carbons of less than 6Å. HMMSTR 3-state secondary structure predictions were 73% correct overall. Tertiary structure predictions did not improve the accuracy of secondary structure prediction.

Availability:The server is accessible through the web at http://isites.bio.rpi.edu/hmmstr/index.html Programs are available upon requests for academics. Licensing agreements are available for commercial interests.

Supplementary information: http://isites.bio.rpi.edu http://predictioncenter.llnl.gov/casp4/

Contact: bystrc{at}rpi.edu shaoy{at}rpi.edu

Keywords: CASP; CAFASP; protein folding; motifs; hidden Markov model; knowledge-based.

* To whom correspondence should be addressed.


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