Search from over 60,000 research works

Advanced Search

Improvement of 3D protein models using multiple templates guided by single-template model quality assessment

Full text not archived in this repository.
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Buenavista, M. T., Roche, D. B. and McGuffin, L. J. orcid id iconORCID: https://orcid.org/0000-0003-4501-4767 (2012) Improvement of 3D protein models using multiple templates guided by single-template model quality assessment. Bioinformatics, 28 (14). pp. 1851-1857. ISSN 1460-2059 doi: 10.1093/bioinformatics/bts292

Abstract/Summary

Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold template is used during the modelling process. However, in many cases, this may also result in poorer model quality for a given target or alignment method. There is a need for modelling protocols that can both consistently and significantly improve 3D models and provide an indication of when models might not benefit from the use of multiple target-template alignments. Here, we investigate the use of both global and local model quality prediction scores produced by ModFOLDclust2, to improve the selection of target-template alignments for the construction of multiple-template models. Additionally, we evaluate clustering the resulting population of multi- and single-template models for the improvement of our IntFOLD-TS tertiary structure prediction method. Results: We find that using accurate local model quality scores to guide alignment selection is the most consistent way to significantly improve models for each of the sequence to structure alignment methods tested. In addition, using accurate global model quality for re-ranking alignments, prior to selection, further improves the majority of multi-template modelling methods tested. Furthermore, subsequent clustering of the resulting population of multiple-template models significantly improves the quality of selected models compared with the previous version of our tertiary structure prediction method, IntFOLD-TS.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/28153
Item Type Article
Refereed Yes
Divisions Life Sciences > School of Biological Sciences > Biomedical Sciences
Publisher Oxford University Press
Download/View statistics View download statistics for this item

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

Search Google Scholar