The authors state no conflict of interest.
Prediction Methods and Reports
Automated tertiary structure prediction with accurate local model quality assessment using the intfold-ts method†
Article first published online: 30 AUG 2011
Copyright © 2011 Wiley-Liss, Inc.
Proteins: Structure, Function, and Bioinformatics
Volume 79, Issue Supplement S10, pages 137–146, 2011
How to Cite
McGuffin, L. J. and Roche, D. B. (2011), Automated tertiary structure prediction with accurate local model quality assessment using the intfold-ts method. Proteins, 79: 137–146. doi: 10.1002/prot.23120
- Issue published online: 9 NOV 2011
- Article first published online: 30 AUG 2011
- Accepted manuscript online: 15 JUL 2011 11:13AM EST
- Manuscript Accepted: 25 MAY 2011
- Manuscript Revised: 12 MAY 2011
- Manuscript Received: 25 MAR 2011
- RCUK Academic Fellowship
- University of Reading Faculty Studentship
- fold recognition, template-based modeling;
- model quality assessment program;
- local model quality prediction;
The IntFOLD-TS method was developed according to the guiding principle that the model quality assessment (QA) would be the most critical stage for our template-based modeling pipeline. Thus, the IntFOLD-TS method firstly generates numerous alternate models, using in-house versions of several different sequence-structure alignment methods, which are then ranked in terms of global quality using our top performing QA method—ModFOLDclust2. In addition to the predicted global quality scores, the predictions of local errors are also provided in the resulting coordinate files, using scores that represent the predicted deviation of each residue in the model from the equivalent residue in the native structure. The IntFOLD-TS method was found to generate high quality 3D models for many of the CASP9 targets, whilst also providing highly accurate predictions of their per-residue errors. This important information may help to make the 3D models that are produced by the IntFOLD-TS method more useful for guiding future experimental work. Proteins 2011; © 2011 Wiley-Liss, Inc.