Analysis of TASSER-based CASP7 protein structure prediction results

Abstract

An improved TASSER (Threading/ASSEmbly/Refinement) methodology is applied to predict the tertiary structure for all CASP7 targets. TASSER employs template identification by threading, followed by tertiary structure assembly by rearranging continuous template fragments, where conformational space is searched via Parallel Hyperbolic Monte Carlo sampling with an optimized force-field that includes knowledge-based statistical potentials and restraints derived from threading templates. The final models are selected by clustering structures from the low temperature replicas. Improvements in TASSER over CASP6 involve use of better templates from 3D-jury applied to three threading programs, PROSPECTOR_3, SP(3), and SPARKS, and a fragment comparison method for better model ranking. For targets with no reliable templates, a variant of TASSER (chunk-TASSER) is also applied with potentials and restraints extracted from ab initio folded supersecondary chunks of the target to build full-length models. For all 124 CASP targets/domains, the average root-mean-square-deviation (RMSD) from native and alignment coverage of the best initial threading models from 3D-jury are 6.2 A and 93%, respectively. Following TASSER reassembly, the average RMSD of the best model in the template aligned region decreases to 4.9 A and the average TM-score increases from 0.617 for the template to 0.678 for the best full-length model. Based on target difficulty, the average TM-scores of the final model to native are 0.904, 0.671, and 0.307 for high-accuracy template-based modeling, template-based modeling, and free modeling targets/domains, respectively. For the more difficult targets, TASSER with modest human intervention performed better in comparison to its server counterpart, MetaTASSER, which used a limited time simulation.

Keywords

Affiliated Institutions

• Georgia Institute of Technology US

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