Title:
Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints
Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints
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Lee, Seung Yup
Skolnick, Jeffrey
Skolnick, Jeffrey
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Abstract
To improve tertiary structure predictions of more difficult targets, the next generation of TASSER, TASSER_2.0, has been developed. TASSER_2.0 incorporates more accurate side-chain contact restraint predictions from a new approach, the composite-sequence method, based on consensus restraints generated by an improved threading algorithm, PROSPECTOR_3.5, which uses computationally evolved and wild-type template sequences as input. TASSER_2.0 was tested on a large-scale, benchmark set of 2591 nonhomologous, single domain proteins " 200 residues that cover the Protein Data Bank at 35% pairwise sequence identity. Compared with the average fraction of accurately predicted side-chain contacts of 0.37 using PROSPECTOR_3.5 with wildtype template sequences, the average accuracy of the composite-sequence method increases to 0.60. The resulting TASSER_2.0 models are closerto their native structures, with an average root mean-square deviation of 4.99 A compared to the 5.31 A result of TASSER. Defining a successful prediction as a model with a root mean-square deviation to native < 6.5 A. the success rate of TASSER_2.0 (TASSER) for Medium targets (targets with good templates/poor alignments) is 74.3% (64.7%) and 40.8% (35.5%) for the Hard targets (incorrect templates/alignments). For Easy targets (good templates/alignments), the success rate slightly increases from 86.3% to 88.4%
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2008-08
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