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Updated: Jul 5, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact
Seung Yup Lee1, Jeffrey Skolnick
1Center for the Study of Systems Biology, Georgia Institute of Technology, Atlanta, Georgia 30318, USA.
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 < or =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 wild-type template sequences, the average accuracy of the composite-sequence method increases to 0.60. The resulting TASSER_2.0 models are closer to 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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