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Ab initio modeling of small proteins by iterative TASSER simulations

BACKGROUND: Predicting 3-dimensional protein structures from amino-acid sequences is an important unsolved problem in computational structural biology. The problem becomes relatively easier if close homologous proteins have been solved, as high-resolution models can be built by aligning target seque...

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Autores principales: Wu, Sitao, Skolnick, Jeffrey, Zhang, Yang
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1878469/
https://www.ncbi.nlm.nih.gov/pubmed/17488521
http://dx.doi.org/10.1186/1741-7007-5-17
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author Wu, Sitao
Skolnick, Jeffrey
Zhang, Yang
author_facet Wu, Sitao
Skolnick, Jeffrey
Zhang, Yang
author_sort Wu, Sitao
collection PubMed
description BACKGROUND: Predicting 3-dimensional protein structures from amino-acid sequences is an important unsolved problem in computational structural biology. The problem becomes relatively easier if close homologous proteins have been solved, as high-resolution models can be built by aligning target sequences to the solved homologous structures. However, for sequences without similar folds in the Protein Data Bank (PDB) library, the models have to be predicted from scratch. Progress in the ab initio structure modeling is slow. The aim of this study was to extend the TASSER (threading/assembly/refinement) method for the ab initio modeling and examine systemically its ability to fold small single-domain proteins. RESULTS: We developed I-TASSER by iteratively implementing the TASSER method, which is used in the folding test of three benchmarks of small proteins. First, data on 16 small proteins (< 90 residues) were used to generate I-TASSER models, which had an average C(α)-root mean square deviation (RMSD) of 3.8Å, with 6 of them having a C(α)-RMSD < 2.5Å. The overall result was comparable with the all-atomic ROSETTA simulation, but the central processing unit (CPU) time by I-TASSER was much shorter (150 CPU days vs. 5 CPU hours). Second, data on 20 small proteins (< 120 residues) were used. I-TASSER folded four of them with a C(α)-RMSD < 2.5Å. The average C(α)-RMSD of the I-TASSER models was 3.9Å, whereas it was 5.9Å using TOUCHSTONE-II software. Finally, 20 non-homologous small proteins (< 120 residues) were taken from the PDB library. An average C(α)-RMSD of 3.9Å was obtained for the third benchmark, with seven cases having a C(α)-RMSD < 2.5Å. CONCLUSION: Our simulation results show that I-TASSER can consistently predict the correct folds and sometimes high-resolution models for small single-domain proteins. Compared with other ab initio modeling methods such as ROSETTA and TOUCHSTONE II, the average performance of I-TASSER is either much better or is similar within a lower computational time. These data, together with the significant performance of automated I-TASSER server (the Zhang-Server) in the 'free modeling' section of the recent Critical Assessment of Structure Prediction (CASP)7 experiment, demonstrate new progresses in automated ab initio model generation. The I-TASSER server is freely available for academic users .
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spelling pubmed-18784692007-05-29 Ab initio modeling of small proteins by iterative TASSER simulations Wu, Sitao Skolnick, Jeffrey Zhang, Yang BMC Biol Research Article BACKGROUND: Predicting 3-dimensional protein structures from amino-acid sequences is an important unsolved problem in computational structural biology. The problem becomes relatively easier if close homologous proteins have been solved, as high-resolution models can be built by aligning target sequences to the solved homologous structures. However, for sequences without similar folds in the Protein Data Bank (PDB) library, the models have to be predicted from scratch. Progress in the ab initio structure modeling is slow. The aim of this study was to extend the TASSER (threading/assembly/refinement) method for the ab initio modeling and examine systemically its ability to fold small single-domain proteins. RESULTS: We developed I-TASSER by iteratively implementing the TASSER method, which is used in the folding test of three benchmarks of small proteins. First, data on 16 small proteins (< 90 residues) were used to generate I-TASSER models, which had an average C(α)-root mean square deviation (RMSD) of 3.8Å, with 6 of them having a C(α)-RMSD < 2.5Å. The overall result was comparable with the all-atomic ROSETTA simulation, but the central processing unit (CPU) time by I-TASSER was much shorter (150 CPU days vs. 5 CPU hours). Second, data on 20 small proteins (< 120 residues) were used. I-TASSER folded four of them with a C(α)-RMSD < 2.5Å. The average C(α)-RMSD of the I-TASSER models was 3.9Å, whereas it was 5.9Å using TOUCHSTONE-II software. Finally, 20 non-homologous small proteins (< 120 residues) were taken from the PDB library. An average C(α)-RMSD of 3.9Å was obtained for the third benchmark, with seven cases having a C(α)-RMSD < 2.5Å. CONCLUSION: Our simulation results show that I-TASSER can consistently predict the correct folds and sometimes high-resolution models for small single-domain proteins. Compared with other ab initio modeling methods such as ROSETTA and TOUCHSTONE II, the average performance of I-TASSER is either much better or is similar within a lower computational time. These data, together with the significant performance of automated I-TASSER server (the Zhang-Server) in the 'free modeling' section of the recent Critical Assessment of Structure Prediction (CASP)7 experiment, demonstrate new progresses in automated ab initio model generation. The I-TASSER server is freely available for academic users . BioMed Central 2007-05-08 /pmc/articles/PMC1878469/ /pubmed/17488521 http://dx.doi.org/10.1186/1741-7007-5-17 Text en Copyright © 2007 Wu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wu, Sitao
Skolnick, Jeffrey
Zhang, Yang
Ab initio modeling of small proteins by iterative TASSER simulations
title Ab initio modeling of small proteins by iterative TASSER simulations
title_full Ab initio modeling of small proteins by iterative TASSER simulations
title_fullStr Ab initio modeling of small proteins by iterative TASSER simulations
title_full_unstemmed Ab initio modeling of small proteins by iterative TASSER simulations
title_short Ab initio modeling of small proteins by iterative TASSER simulations
title_sort ab initio modeling of small proteins by iterative tasser simulations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1878469/
https://www.ncbi.nlm.nih.gov/pubmed/17488521
http://dx.doi.org/10.1186/1741-7007-5-17
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