The authors state no conflict of interest.
Prediction Methods and Reports
Raptorx: Exploiting structure information for protein alignment by statistical inference †
Article first published online: 11 OCT 2011
Copyright © 2011 Wiley-Liss, Inc.
Proteins: Structure, Function, and Bioinformatics
Volume 79, Issue Supplement S10, pages 161–171, 2011
How to Cite
Peng, J. and Xu, J. (2011), Raptorx: Exploiting structure information for protein alignment by statistical inference . Proteins, 79: 161–171. doi: 10.1002/prot.23175
- Issue published online: 9 NOV 2011
- Article first published online: 11 OCT 2011
- Accepted manuscript online: 12 SEP 2011 01:23AM EST
- Manuscript Accepted: 19 AUG 2011
- Manuscript Revised: 25 JUL 2011
- Manuscript Received: 6 APR 2011
- National Institutes of Health. Grant Number: R01GM089753
- National Science Foundation. Grant Number: DBI-0960390
- single-template threading;
- multiple-template threading;
- alignment quality prediction;
- probabilistic alignment;
- multiple protein alignment;
This work presents RaptorX, a statistical method for template-based protein modeling that improves alignment accuracy by exploiting structural information in a single or multiple templates. RaptorX consists of three major components: single-template threading, alignment quality prediction, and multiple-template threading. This work summarizes the methods used by RaptorX and presents its CASP9 result analysis, aiming to identify major bottlenecks with RaptorX and template-based modeling and hopefully directions for further study. Our results show that template structural information helps a lot with both single-template and multiple-template protein threading especially when closely-related templates are unavailable, and there is still large room for improvement in both alignment and template selection. The RaptorX web server is available at http://raptorx.uchicago.edu. Proteins 2011; © 2011 Wiley-Liss, Inc.