The authors state no conflict of interest.
Template Based Assessment
Assessment of template based protein structure predictions in CASP9†
Article first published online: 15 OCT 2011
Copyright © 2011 Wiley-Liss, Inc.
Proteins: Structure, Function, and Bioinformatics
Volume 79, Issue Supplement S10, pages 37–58, 2011
How to Cite
Mariani, V., Kiefer, F., Schmidt, T., Haas, J. and Schwede, T. (2011), Assessment of template based protein structure predictions in CASP9. Proteins, 79: 37–58. doi: 10.1002/prot.23177
- Issue published online: 9 NOV 2011
- Article first published online: 15 OCT 2011
- Accepted manuscript online: 14 SEP 2011 04:04PM EST
- Manuscript Accepted: 4 SEP 2011
- Manuscript Revised: 1 SEP 2011
- Manuscript Received: 24 JUN 2011
- protein structure;
- structure prediction;
In the Ninth Edition of the Critical Assessment of Techniques for Protein Structure Prediction (CASP9), 61,665 models submitted by 176 groups were assessed for their accuracy in the template based modeling category. The models were evaluated numerically in comparison to their experimental control structures using two global measures (GDT and GDC), and a novel local score evaluating the correct modeling of local interactions (lDDT). Overall, the state of the art of template based modeling in CASP9 is high, with many groups performing well. Among the methods registered as prediction “servers”, six independent groups are performing on average better than the rest. The submissions by “human” groups are dominated by meta-predictors, with one group performing noticeably better than the others. Most of the participating groups failed to assign realistic confidence estimates to their predictions, and only a very small fraction of the assessed methods have provided highly accurate models and realistic error estimates at the same time. Also, the accuracy of predictions for homo-oligomeric assemblies was overall poor, and only one group performed better than a naïve control predictor. Here, we present the results of our assessment of the CASP9 predictions in the category of template based modeling, documenting the state of the art and highlighting areas for future developments. Proteins 2011; © 2011 Wiley-Liss, Inc.