Raptorx: Exploiting structure information for protein alignment by statistical inference

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Abstract
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;