Template-based protein structure modeling using TASSER(VMT.)

Abstract

Template-based protein structure modeling is commonly used for protein structure prediction. Based on the observation that multiple template-based methods often perform better than single template-based methods, we further explore the use of a variable number of multiple templates for a given target in the latest variant of TASSER, TASSER(VMT) . We first develop an algorithm that improves the target-template alignment for a given template. The improved alignment, called the SP(3) alternative alignment, is generated by a parametric alignment method coupled with short TASSER refinement on models selected using knowledge-based scores. The refined top model is then structurally aligned to the template to produce the SP(3) alternative alignment. Templates identified using SP(3) threading are combined with the SP(3) alternative and HHEARCH alignments to provide target alignments to each template. These template models are then grouped into sets containing a variable number of template/alignment combinations. For each set, we run short TASSER simulations to build full-length models. Then, the models from all sets of templates are pooled, and the top 20-50 models selected using FTCOM ranking method. These models are then subjected to a single longer TASSER refinement run for final prediction. We benchmarked our method by comparison with our previously developed approach, pro-sp(3) -TASSER, on a set with 874 easy and 318 hard targets. The average GDT-TS score improvements for the first model are 3.5 and 4.3% for easy and hard targets, respectively. When tested on the 112 CASP9 targets, our method improves the average GDT-TS scores as compared to pro-sp3-TASSER by 8.2 and 9.3% for the 80 easy and 32 hard targets, respectively. It also shows slightly better results than the top ranked CASP9 Zhang-Server, QUARK and HHpredA methods. The program is available for download at http://cssb.biology.gatech.edu/.

Keywords: SP3; TASSER; alignment; template-based modeling; threading.

Figure 1

(a) Flowchart of TASSER^VMT (b) Flowchart of SP³ alternative alignment generation.

Figure 2

Scatter plot comparison of the first model’s GDT-TS scores by pro-sp3-TASSER and TASSER^VMT on the 1192 protein benchmark target set. The number of targets for which TASSER^VMT is better/worse than pro-sp3-TASSER is 765/397.

Figure 3

Histogram comparison of first model GDT-TS score by pro-sp3-TASSER and TASSER^VMT on the 1192 target set. (a) Easy set; (b) Hard set. The y-axis is the number of targets having first model GDT-TS score > x.

Figure 4

Examples of TASSER^VMT improvement over pro-sp3-TASSER models. Numbers in parenthesis are GDT-TS scores to native. TASSER models are also shown for comparison.