Literature DB >> 16963505

TASSER-Lite: an automated tool for protein comparative modeling.

Shashi Bhushan Pandit1, Yang Zhang, Jeffrey Skolnick.   

Abstract

This study involves the development of a rapid comparative modeling tool for homologous sequences by extension of the TASSER methodology, developed for tertiary structure prediction. This comparative modeling procedure was validated on a representative benchmark set of proteins in the Protein Data Bank composed of 901 single domain proteins (41-200 residues) having sequence identities between 35-90% with respect to the template. Using a Monte Carlo search scheme with the length of runs optimized for weakly/nonhomologous proteins, TASSER often provides appreciable improvement in structure quality over the initial template. However, on average, this requires approximately 29 h of CPU time per sequence. Since homologous proteins are unlikely to require the extent of conformational search as weakly/nonhomologous proteins, TASSER's parameters were optimized to reduce the required CPU time to approximately 17 min, while retaining TASSER's ability to improve structure quality. Using this optimized TASSER (TASSER-Lite), we find an average improvement in the aligned region of approximately 10% in root mean-square deviation from native over the initial template. Comparison of TASSER-Lite with the widely used comparative modeling tool MODELLER showed that TASSER-Lite yields final models that are closer to the native. TASSER-Lite is provided on the web at (http://cssb.biology.gatech.edu/skolnick/webservice/tasserlite/index.html).

Mesh:

Year:  2006        PMID: 16963505      PMCID: PMC1635668          DOI: 10.1529/biophysj.106.084293

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  42 in total

1.  The Protein Data Bank.

Authors:  H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Combination of threading potentials and sequence profiles improves fold recognition.

Authors:  A R Panchenko; A Marchler-Bauer; S H Bryant
Journal:  J Mol Biol       Date:  2000-03-10       Impact factor: 5.469

3.  Development and large scale benchmark testing of the PROSPECTOR_3 threading algorithm.

Authors:  Jeffrey Skolnick; Daisuke Kihara; Yang Zhang
Journal:  Proteins       Date:  2004-08-15

4.  Accurate modeling of protein conformation by automatic segment matching.

Authors:  M Levitt
Journal:  J Mol Biol       Date:  1992-07-20       Impact factor: 5.469

5.  A method to identify protein sequences that fold into a known three-dimensional structure.

Authors:  J U Bowie; R Lüthy; D Eisenberg
Journal:  Science       Date:  1991-07-12       Impact factor: 47.728

6.  Modelling the polypeptide backbone with 'spare parts' from known protein structures.

Authors:  M Claessens; E Van Cutsem; I Lasters; S Wodak
Journal:  Protein Eng       Date:  1989-01

Review 7.  Knowledge-based prediction of protein structures and the design of novel molecules.

Authors:  T L Blundell; B L Sibanda; M J Sternberg; J M Thornton
Journal:  Nature       Date:  1987 Mar 26-Apr 1       Impact factor: 49.962

8.  An evaluation of the performance of an automated procedure for comparative modelling of protein tertiary structure.

Authors:  N Srinivasan; T L Blundell
Journal:  Protein Eng       Date:  1993-07

9.  Comparative protein modelling by satisfaction of spatial restraints.

Authors:  A Sali; T L Blundell
Journal:  J Mol Biol       Date:  1993-12-05       Impact factor: 5.469

10.  An automated method for modeling proteins on known templates using distance geometry.

Authors:  S Srinivasan; C J March; S Sudarsanam
Journal:  Protein Sci       Date:  1993-02       Impact factor: 6.725

View more
  18 in total

1.  Ab initio protein structure prediction using chunk-TASSER.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  Biophys J       Date:  2007-05-11       Impact factor: 4.033

2.  Protein structure prediction by pro-Sp3-TASSER.

Authors:  Hongyi Zhou; Jeffrey Skolnick
Journal:  Biophys J       Date:  2009-03-18       Impact factor: 4.033

3.  eFindSite: improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands.

Authors:  Michal Brylinski; Wei P Feinstein
Journal:  J Comput Aided Mol Des       Date:  2013-07-10       Impact factor: 3.686

4.  PSiFR: an integrated resource for prediction of protein structure and function.

Authors:  Shashi B Pandit; Michal Brylinski; Hongyi Zhou; Mu Gao; Adrian K Arakaki; Jeffrey Skolnick
Journal:  Bioinformatics       Date:  2010-01-14       Impact factor: 6.937

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

Authors:  Seung Yup Lee; Jeffrey Skolnick
Journal:  Biophys J       Date:  2008-05-16       Impact factor: 4.033

6.  Novel protein folds and their nonsequential structural analogs.

Authors:  Aysam Guerler; Ernst-Walter Knapp
Journal:  Protein Sci       Date:  2008-06-26       Impact factor: 6.725

7.  RaptorX: exploiting structure information for protein alignment by statistical inference.

Authors:  Jian Peng; Jinbo Xu
Journal:  Proteins       Date:  2011-10-11

8.  A comparison of different functions for predicted protein model quality assessment.

Authors:  Juan Li; Huisheng Fang
Journal:  J Comput Aided Mol Des       Date:  2016-08-03       Impact factor: 3.686

Review 9.  Template-based protein modeling: recent methodological advances.

Authors:  Pankaj R Daga; Ronak Y Patel; Robert J Doerksen
Journal:  Curr Top Med Chem       Date:  2010       Impact factor: 3.295

10.  Performance of the Pro-sp3-TASSER server in CASP8.

Authors:  Hongyi Zhou; Shashi B Pandit; Jeffrey Skolnick
Journal:  Proteins       Date:  2009
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.