Limits...
i3Drefine software for protein 3D structure refinement and its assessment in CASP10.

Bhattacharya D, Cheng J - PLoS ONE (2013)

Bottom Line: During the 9(th) and recently concluded 10(th) CASP experiments, a consistent growth in number of refinement targets and participating groups has been witnessed.Yet, protein structure refinement still remains a largely unsolved problem with majority of participating groups in CASP refinement category failed to consistently improve the quality of structures issued for refinement.Our analysis demonstrates that i3Drefine is only fully-automated server participating in CASP10 exhibiting consistent improvement over the initial structures in both global and local structural quality metrics.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Missouri, Columbia, Missouri, United States of America.

ABSTRACT
Protein structure refinement refers to the process of improving the qualities of protein structures during structure modeling processes to bring them closer to their native states. Structure refinement has been drawing increasing attention in the community-wide Critical Assessment of techniques for Protein Structure prediction (CASP) experiments since its addition in 8(th) CASP experiment. During the 9(th) and recently concluded 10(th) CASP experiments, a consistent growth in number of refinement targets and participating groups has been witnessed. Yet, protein structure refinement still remains a largely unsolved problem with majority of participating groups in CASP refinement category failed to consistently improve the quality of structures issued for refinement. In order to alleviate this need, we developed a completely automated and computationally efficient protein 3D structure refinement method, i3Drefine, based on an iterative and highly convergent energy minimization algorithm with a powerful all-atom composite physics and knowledge-based force fields and hydrogen bonding (HB) network optimization technique. In the recent community-wide blind experiment, CASP10, i3Drefine (as 'MULTICOM-CONSTRUCT') was ranked as the best method in the server section as per the official assessment of CASP10 experiment. Here we provide the community with free access to i3Drefine software and systematically analyse the performance of i3Drefine in strict blind mode on the refinement targets issued in CASP10 refinement category and compare with other state-of-the-art refinement methods participating in CASP10. Our analysis demonstrates that i3Drefine is only fully-automated server participating in CASP10 exhibiting consistent improvement over the initial structures in both global and local structural quality metrics. Executable version of i3Drefine is freely available at http://protein.rnet.missouri.edu/i3drefine/.

Show MeSH
Quartile plots of score changes with respect to the quality of starting structures for top human predictors and i3Drefine.Quartile plots of score changes relative to starting models for 5 human predictors and i3Drefine are shown for these metrics: (A) GDT-TS, (B) RMSD, (C) GDC-SC, (D) MolProbity, (E) SphereGrinder and (F) CAD-AA. The points outside the boxes indicate the outliers.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3716612&req=5

pone-0069648-g008: Quartile plots of score changes with respect to the quality of starting structures for top human predictors and i3Drefine.Quartile plots of score changes relative to starting models for 5 human predictors and i3Drefine are shown for these metrics: (A) GDT-TS, (B) RMSD, (C) GDC-SC, (D) MolProbity, (E) SphereGrinder and (F) CAD-AA. The points outside the boxes indicate the outliers.

Mentions: Figure 8 shows the quartile plots of change in model quality relative to the starting model in six quality metrics for all submitted model by top five human predictors as per the official CASP10 results released during CASP10 meeting and i3Drefine for all CASP10 refinement targets. The most obvious added benefit of human predictors is the ability to perform large improvement in model quality. Groups like FEIG, Seok, Mufold and FLOUDAS seem to perform large changes in starting structures. Although the degree of refinement in these adventurous refinement strategies are much more pronounced than i3Drefine, these methods often lack the ability to perform consistent improvement. Encouragingly, the ability of i3Drefine to perform steady and consistent improvement is noticeable even when it is compared with non-server methods participating in CASP10 refinement experiment. Majority of the times, i3Drefine improves all the quality scores except MolProbity. KnowMIN protocol seems to be more conservative refinement approach than other top-performing human groups. Except SphereGrinder, KnowMIN group improves in the other quality metrics consistently. Among the top-performing human predictors, FEIG group is particularly noteworthy in its ability to improve the backbone positioning as measured by GDT-TS score accompanied by enhancement in local quality measures like MolProbity and CAD-AA. This is possibly achieved through a broader sampling around the starting model. It has to be noted, however, that the human predictors were given three weeks deadline to submit the refined structures to the prediction centre as opposed to three days deadline offered for the server methods and there might be significant human intervention involved in the non-server prediction primarily because of the relaxed submission window. A server group like MULTICOM-CONSTRUCT (i3Drefine), on the other hand, has to be completely automated in order to meet the submission deadline. It is, therefore, unfair to directly compare a server method with human groups especially when the turnaround time for a human predictor is not known. Nevertheless, the ability of human predictors to perform larger improvement can advance the field of protein structure refinement, thereby enhancing the accuracy of contemporary computational protein structure prediction methods provided these methods can be automated providing the prediction within a reasonable amount of time. In addition to being directly implemented in an automated server, human predictors in the CASP experiments often generate valuable insights and guidance for improving protein structure refinement in general.


i3Drefine software for protein 3D structure refinement and its assessment in CASP10.

Bhattacharya D, Cheng J - PLoS ONE (2013)

Quartile plots of score changes with respect to the quality of starting structures for top human predictors and i3Drefine.Quartile plots of score changes relative to starting models for 5 human predictors and i3Drefine are shown for these metrics: (A) GDT-TS, (B) RMSD, (C) GDC-SC, (D) MolProbity, (E) SphereGrinder and (F) CAD-AA. The points outside the boxes indicate the outliers.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3716612&req=5

pone-0069648-g008: Quartile plots of score changes with respect to the quality of starting structures for top human predictors and i3Drefine.Quartile plots of score changes relative to starting models for 5 human predictors and i3Drefine are shown for these metrics: (A) GDT-TS, (B) RMSD, (C) GDC-SC, (D) MolProbity, (E) SphereGrinder and (F) CAD-AA. The points outside the boxes indicate the outliers.
Mentions: Figure 8 shows the quartile plots of change in model quality relative to the starting model in six quality metrics for all submitted model by top five human predictors as per the official CASP10 results released during CASP10 meeting and i3Drefine for all CASP10 refinement targets. The most obvious added benefit of human predictors is the ability to perform large improvement in model quality. Groups like FEIG, Seok, Mufold and FLOUDAS seem to perform large changes in starting structures. Although the degree of refinement in these adventurous refinement strategies are much more pronounced than i3Drefine, these methods often lack the ability to perform consistent improvement. Encouragingly, the ability of i3Drefine to perform steady and consistent improvement is noticeable even when it is compared with non-server methods participating in CASP10 refinement experiment. Majority of the times, i3Drefine improves all the quality scores except MolProbity. KnowMIN protocol seems to be more conservative refinement approach than other top-performing human groups. Except SphereGrinder, KnowMIN group improves in the other quality metrics consistently. Among the top-performing human predictors, FEIG group is particularly noteworthy in its ability to improve the backbone positioning as measured by GDT-TS score accompanied by enhancement in local quality measures like MolProbity and CAD-AA. This is possibly achieved through a broader sampling around the starting model. It has to be noted, however, that the human predictors were given three weeks deadline to submit the refined structures to the prediction centre as opposed to three days deadline offered for the server methods and there might be significant human intervention involved in the non-server prediction primarily because of the relaxed submission window. A server group like MULTICOM-CONSTRUCT (i3Drefine), on the other hand, has to be completely automated in order to meet the submission deadline. It is, therefore, unfair to directly compare a server method with human groups especially when the turnaround time for a human predictor is not known. Nevertheless, the ability of human predictors to perform larger improvement can advance the field of protein structure refinement, thereby enhancing the accuracy of contemporary computational protein structure prediction methods provided these methods can be automated providing the prediction within a reasonable amount of time. In addition to being directly implemented in an automated server, human predictors in the CASP experiments often generate valuable insights and guidance for improving protein structure refinement in general.

Bottom Line: During the 9(th) and recently concluded 10(th) CASP experiments, a consistent growth in number of refinement targets and participating groups has been witnessed.Yet, protein structure refinement still remains a largely unsolved problem with majority of participating groups in CASP refinement category failed to consistently improve the quality of structures issued for refinement.Our analysis demonstrates that i3Drefine is only fully-automated server participating in CASP10 exhibiting consistent improvement over the initial structures in both global and local structural quality metrics.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Missouri, Columbia, Missouri, United States of America.

ABSTRACT
Protein structure refinement refers to the process of improving the qualities of protein structures during structure modeling processes to bring them closer to their native states. Structure refinement has been drawing increasing attention in the community-wide Critical Assessment of techniques for Protein Structure prediction (CASP) experiments since its addition in 8(th) CASP experiment. During the 9(th) and recently concluded 10(th) CASP experiments, a consistent growth in number of refinement targets and participating groups has been witnessed. Yet, protein structure refinement still remains a largely unsolved problem with majority of participating groups in CASP refinement category failed to consistently improve the quality of structures issued for refinement. In order to alleviate this need, we developed a completely automated and computationally efficient protein 3D structure refinement method, i3Drefine, based on an iterative and highly convergent energy minimization algorithm with a powerful all-atom composite physics and knowledge-based force fields and hydrogen bonding (HB) network optimization technique. In the recent community-wide blind experiment, CASP10, i3Drefine (as 'MULTICOM-CONSTRUCT') was ranked as the best method in the server section as per the official assessment of CASP10 experiment. Here we provide the community with free access to i3Drefine software and systematically analyse the performance of i3Drefine in strict blind mode on the refinement targets issued in CASP10 refinement category and compare with other state-of-the-art refinement methods participating in CASP10. Our analysis demonstrates that i3Drefine is only fully-automated server participating in CASP10 exhibiting consistent improvement over the initial structures in both global and local structural quality metrics. Executable version of i3Drefine is freely available at http://protein.rnet.missouri.edu/i3drefine/.

Show MeSH