Accessibility navigation


Improving sequence-based fold recognition by using 3D model quality assessment

Pettitt, C. S., McGuffin, L. J. and Jones, D. T. (2005) Improving sequence-based fold recognition by using 3D model quality assessment. Bioinformatics, 21 (17). pp. 3509-3515. ISSN 1460-2059

Full text not archived in this repository.

To link to this article DOI: 10.1093/bioinformatics/bti540

Abstract/Summary

Motivation: The ability of a simple method (MODCHECK) to determine the sequence–structure compatibility of a set of structural models generated by fold recognition is tested in a thorough benchmark analysis. Four Model Quality Assessment Programs (MQAPs) were tested on 188 targets from the latest LiveBench-9 automated structure evaluation experiment. We systematically test and evaluate whether the MQAP methods can successfully detect native-likemodels. Results: We show that compared with the other three methods tested MODCHECK is the most reliable method for consistently performing the best top model selection and for ranking the models. In addition, we show that the choice of model similarity score used to assess a model's similarity to the experimental structure can influence the overall performance of these tools. Although these MQAP methods fail to improve the model selection performance for methods that already incorporate protein three dimension (3D) structural information, an improvement is observed for methods that are purely sequence-based, including the best profile–profile methods. This suggests that even the best sequence-based fold recognition methods can still be improved by taking into account the 3D structural information.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Biological Sciences > Biomedical Sciences
No Reading authors. Back catalogue items
ID Code:27421
Publisher:Oxford University Press

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation