The authors state no conflict of interest.
Prediction of global and local quality of CASP8 models by MULTICOM series†
Article first published online: 28 MAY 2009
Copyright © 2009 Wiley-Liss, Inc.
Proteins: Structure, Function, and Bioinformatics
Volume 77, Issue Supplement S9, pages 181–184, 2009
How to Cite
Cheng, J., Wang, Z., Tegge, A. N. and Eickholt, J. (2009), Prediction of global and local quality of CASP8 models by MULTICOM series. Proteins, 77: 181–184. doi: 10.1002/prot.22487
- Issue published online: 22 OCT 2009
- Article first published online: 28 MAY 2009
- Accepted manuscript online: 28 MAY 2009 12:00AM EST
- Manuscript Accepted: 12 MAY 2009
- Manuscript Revised: 27 APR 2009
- Manuscript Received: 11 MAR 2009
- MU Bioinformatics Consortium
- UM research board grant
- MU research council grant
- NLM fellowship
- protein structure prediction;
- protein model quality assessment;
- model quality assurance program;
Evaluating the quality of protein structure models is important for selecting and using models. Here, we describe the MULTICOM series of model quality predictors which contains three predictors tested in the CASP8 experiments. We evaluated these predictors on 120 CASP8 targets. The average correlations between predicted and real GDT-TS scores of the two semi-clustering methods (MULTICOM and MULTICOM-CLUSTER) and the one single-model ab initio method (MULTICOM-CMFR) are 0.90, 0.89, and 0.74, respectively; and their average difference (or GDT-TS loss) between the global GDT-TS scores of the top-ranked models and the best models are 0.05, 0.06, and 0.07, respectively. The average correlation between predicted and real local quality scores of the semi-clustering methods is above 0.64. Our results show that the novel semi-clustering approach that compares a model with top ranked reference models can improve initial quality scores generated by the ab initio method and a simple meta approach. Proteins 2009. © 2009 Wiley-Liss, Inc.