RaptorX is a protein structure prediction server developed by Xu group, excelling at predicting 3D structures for protein sequences without close homologs in the Protein Data Bank (PDB). Given an input sequence, RaptorX predicts its secondary and tertiary structures as well as solvent accessibility and disordered regions. RaptorX also assigns the following confidence scores to indicate the quality of a predicted 3D model: P-value for the relative global quality, GDT (global distance test) and uGDT (un-normalized GDT) for the absolute global quality, and RMSD for the absolute local quality of each residue in the model. RaptorX-Binding is a web server that predicts the binding sites of a protein sequence, based upon the predicted 3D model by RaptorX.
Please see the publications listed below for more method details.
RaptorX performance in CASP9
RaptorX excels at the alignment of hard targets, which have less than 30% sequence identity with solved structures in PDB. As shown in the below figure, blindly tested on the 50 hardest CASP9 template-based modeling targets, RaptorX outperforms all the CASP9 participating servers including those using consensus and refinement methods.
The above figure shows the performance of top 25 groups on the 50 hardest CASP9 TBM targets. X: group numbers. Y: the number of top 25 groups outperformed by a given group. The figure is taken from the CASP9 assessor’s presentation at http://predictioncenter.org/casp9/doc/presentations/CASP9_TBM.pdf
Citing RaptorXPlease acknowledge the use of RaptorX in any of your work by citing our publication Nature Methods paper:
Morten Källberg, Haipeng Wang, Sheng Wang, Jian Peng, Zhiyong Wang, Hui Lu & Jinbo Xu. Template-based protein structure modeling using the RaptorX web server. Nature Protocols 7, 1511–1522, 2012.Other Publication
Jian Peng and Jinbo Xu. RaptorX: exploiting structure information for protein alignment by statistical inference. PROTEINS, 2011.
Jian Peng and Jinbo Xu. A multiple-template approach to protein threading. PROTEINS, 2011.
Jian Peng and Jinbo Xu. Boosting protein threading accuracy. In the Proceedings of the 13th International Conference on Research in Computational Molecular Biology (RECOMB), Lecture Notes in Computer Science. Vol. 5541, pp. 31-45, 2009. Springer.
Jian Peng and Jinbo Xu. Low-homology protein threading. Bioinformatics (Proceedings of ISMB 2010), 2010.
Feng Zhao, Jian Peng and Jinbo Xu. Fragment-free approach to protein folding using conditional neural fields. Bioinformatics (Proceedings of ISMB 2010), 2010.
Feng Zhao, Jian Peng, Joe DeBartolo, Karl F. Freed, Tobin R. Sosnick and Jinbo Xu. A probabilistic and continuous model of protein conformational space for template-free modeling. Journal of Computational Biology, 2010.
RaptorX Storage for Publication
In general jobs will be deleted from the server two weeks after completion due to limited storage capacity. We do, however, recognize that user may want to refer to their results from the server in published work and further, make these results available to the public.
To request that a specific set of results be stored permanently on the server and/or be made publicly available please contact us.