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Ab initio modeling of small proteins by iterative TASSER simulations.

Wu S, Skolnick J, Zhang Y - BMC Biol. (2007)

Bottom Line: 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).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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Bioinformatics and Department of Molecular Bioscience, University of Kansas, Lawrence, KS 66047, USA. stwu@ku.edu

ABSTRACT

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 Calpha-root mean square deviation (RMSD) of 3.8A, with 6 of them having a Calpha-RMSD < 2.5A. 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 Calpha-RMSD < 2.5A. The average Calpha-RMSD of the I-TASSER models was 3.9A, whereas it was 5.9A using TOUCHSTONE-II software. Finally, 20 non-homologous small proteins (< 120 residues) were taken from the PDB library. An average Calpha-RMSD of 3.9A was obtained for the third benchmark, with seven cases having a Calpha-RMSD < 2.5A.

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 http://zhang.bioinformatics.ku.edu/I-TASSER.

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Comparison of I-TASSER models with the PPA threading alignment results. (A) Cα-RMSD to native of the I-TASSER models versus Cα-RMSD to native of the best threading alignment over the same aligned regions. (B) TM-score of the I-TASSER models versus TM-score of the best threading alignments.
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Figure 3: Comparison of I-TASSER models with the PPA threading alignment results. (A) Cα-RMSD to native of the I-TASSER models versus Cα-RMSD to native of the best threading alignment over the same aligned regions. (B) TM-score of the I-TASSER models versus TM-score of the best threading alignments.

Mentions: Figure 3A shows the plot of Cα-RMSD to native of the best model in the top five clusters versus that of the best threading alignments over the same aligned regions (star symbols). Almost all the final models (except 1b72A) were much closer to native than the best threading alignments, as indicated by the reduction of RMSD values. Along the same aligned region, the average Cα-RMSD for the models and the templates were 3.6Å and 5.7Å respectively. The significant improvement of I-TASSER models on the threading alignments were also found here (Figure 3B), where the average TM-score for the models and the template were 0.61 and 0.49 respectively. Again, most of final models had a higher TM-score than that of the best threading alignments (a list of the best templates with the highest TM-score for each target protein in this study is available online at ).


Ab initio modeling of small proteins by iterative TASSER simulations.

Wu S, Skolnick J, Zhang Y - BMC Biol. (2007)

Comparison of I-TASSER models with the PPA threading alignment results. (A) Cα-RMSD to native of the I-TASSER models versus Cα-RMSD to native of the best threading alignment over the same aligned regions. (B) TM-score of the I-TASSER models versus TM-score of the best threading alignments.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1878469&req=5

Figure 3: Comparison of I-TASSER models with the PPA threading alignment results. (A) Cα-RMSD to native of the I-TASSER models versus Cα-RMSD to native of the best threading alignment over the same aligned regions. (B) TM-score of the I-TASSER models versus TM-score of the best threading alignments.
Mentions: Figure 3A shows the plot of Cα-RMSD to native of the best model in the top five clusters versus that of the best threading alignments over the same aligned regions (star symbols). Almost all the final models (except 1b72A) were much closer to native than the best threading alignments, as indicated by the reduction of RMSD values. Along the same aligned region, the average Cα-RMSD for the models and the templates were 3.6Å and 5.7Å respectively. The significant improvement of I-TASSER models on the threading alignments were also found here (Figure 3B), where the average TM-score for the models and the template were 0.61 and 0.49 respectively. Again, most of final models had a higher TM-score than that of the best threading alignments (a list of the best templates with the highest TM-score for each target protein in this study is available online at ).

Bottom Line: 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).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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Bioinformatics and Department of Molecular Bioscience, University of Kansas, Lawrence, KS 66047, USA. stwu@ku.edu

ABSTRACT

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 Calpha-root mean square deviation (RMSD) of 3.8A, with 6 of them having a Calpha-RMSD < 2.5A. 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 Calpha-RMSD < 2.5A. The average Calpha-RMSD of the I-TASSER models was 3.9A, whereas it was 5.9A using TOUCHSTONE-II software. Finally, 20 non-homologous small proteins (< 120 residues) were taken from the PDB library. An average Calpha-RMSD of 3.9A was obtained for the third benchmark, with seven cases having a Calpha-RMSD < 2.5A.

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 http://zhang.bioinformatics.ku.edu/I-TASSER.

Show MeSH
Related in: MedlinePlus