Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints |
| |
Authors: | Lee Seung Yup Skolnick Jeffrey |
| |
Institution: | Center for the Study of Systems Biology, Georgia Institute of Technology, Atlanta, Georgia 30318 |
| |
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 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 Å compared to the 5.31 Å result of TASSER. Defining a successful prediction as a model with a root mean-square deviation to native <6.5 Å, 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%. |
| |
Keywords: | |
本文献已被 ScienceDirect PubMed 等数据库收录! |
|