Raptorx: Exploiting structure information for protein alignment by statistical inference

Jian Peng, Jinbo Xu

Research output: Contribution to journalArticlepeer-review


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. Proteins 2011;

Original languageEnglish (US)
Pages (from-to)161-171
Number of pages11
JournalProteins: Structure, Function and Bioinformatics
Issue numberSUPPL. 10
StatePublished - 2011
Externally publishedYes


  • Alignment quality prediction
  • CASP
  • Multiple protein alignment
  • Multiple-template threading
  • Probabilistic alignment
  • Single-template threading

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology


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