Title:
Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints

dc.contributor.author Lee, Seung Yup
dc.contributor.author Skolnick, Jeffrey
dc.contributor.corporatename Georgia Institute of Technology. Center for the Study of Systems Biology
dc.contributor.corporatename Georgia Institute of Technology. School of Biology
dc.date.accessioned 2011-10-28T19:33:30Z
dc.date.available 2011-10-28T19:33:30Z
dc.date.issued 2008-08
dc.description © 2008 by the Biophysical Society en_US
dc.description.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% en
dc.identifier.citation Lee, SY, Skolnick J. 2008. Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints. Biophysical journal. 95(4):1956-64. en
dc.identifier.issn 0006-3495
dc.identifier.uri http://hdl.handle.net/1853/41937
dc.language.iso en_US en
dc.publisher Georgia Institute of Technology en
dc.publisher.original Biophysical Society
dc.subject Tertiary structure predictions en
dc.subject TASSER 2.0 en
dc.subject Protein structure prediction algorithm en
dc.title Benchmarking of TASSER_2.0: an improved protein structure prediction algorithm with more accurate predicted contact restraints en
dc.type Text
dc.type.genre Article
dspace.entity.type Publication
local.contributor.author Skolnick, Jeffrey
local.contributor.corporatename College of Sciences
local.contributor.corporatename School of Biological Sciences
local.contributor.corporatename Center for the Study of Systems Biology
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