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Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method

McGuffin, L. J. and Roche, D. B. (2011) Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method. Proteins: Structure, Function, and Bioinformatics, 79 (S10). pp. 137-146. ISSN 1097-0134

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To link to this article DOI: 10.1002/prot.23120

Abstract/Summary

The IntFOLD-TS method was developed according to the guiding principle that the model quality assessment would be the most critical stage for our template based modelling pipeline. Thus, the IntFOLD-TS method firstly generates numerous alternative 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 quality assessment 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

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Biological Sciences > Biomedical Sciences
Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR)
ID Code:22565
Uncontrolled Keywords:Fold Recognition; Template Based Modelling; Model Quality Assessment Program; Local Model Quality Prediction; Clustering
Additional Information:Supplement S10 Proteins
Publisher:Wiley

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