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A resource for benchmarking the usefulness of protein structure models.

Carbajo D, Tramontano A - BMC Bioinformatics (2012)

Bottom Line: The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest.The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively.Any restrictions to use by non-academics: No.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physics, Sapienza University of Rome, P,le A, Moro, 5, 00185 Rome, Italy.

ABSTRACT

Background: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application.

Results: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively.

Conclusions: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

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ModelDB result page. The structure of T4 lysozyme chain A (PDB code [PDB:118 l]) and of one of its decoy models (the third sorted according to HHsearch [14] score of the template used) are displayed in the Jmol window as cartoons and colored according to solvent accessibilities. For the model, the transparent solvent excluded surface is also shown. A ligand binding Isoleucine is highlighted in both structures, as well as in the most accurate model for the same protein. The Isoleucine in one of the models is predicted to be in an incorrectly modeled loop, far away from its correct position.
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Figure 3: ModelDB result page. The structure of T4 lysozyme chain A (PDB code [PDB:118 l]) and of one of its decoy models (the third sorted according to HHsearch [14] score of the template used) are displayed in the Jmol window as cartoons and colored according to solvent accessibilities. For the model, the transparent solvent excluded surface is also shown. A ligand binding Isoleucine is highlighted in both structures, as well as in the most accurate model for the same protein. The Isoleucine in one of the models is predicted to be in an incorrectly modeled loop, far away from its correct position.

Mentions: The page contains a short description of the protein and a sortable table (Figure 3B) where the models are listed and can be ranked. One or more models can be visualized using a Jmol applet (Figure 3A) and are shown superimposed to the experimental structure. Different representations are possible (cartoons, spacefill, trace, backbone representations, etc.) and solvent excluded and solvent accessible surfaces can be rendered. A state win-dow records what happens in the Jmol applet (Figure 3C). The user can also rotate the axes in the Jmol window and create images.


A resource for benchmarking the usefulness of protein structure models.

Carbajo D, Tramontano A - BMC Bioinformatics (2012)

ModelDB result page. The structure of T4 lysozyme chain A (PDB code [PDB:118 l]) and of one of its decoy models (the third sorted according to HHsearch [14] score of the template used) are displayed in the Jmol window as cartoons and colored according to solvent accessibilities. For the model, the transparent solvent excluded surface is also shown. A ligand binding Isoleucine is highlighted in both structures, as well as in the most accurate model for the same protein. The Isoleucine in one of the models is predicted to be in an incorrectly modeled loop, far away from its correct position.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3473236&req=5

Figure 3: ModelDB result page. The structure of T4 lysozyme chain A (PDB code [PDB:118 l]) and of one of its decoy models (the third sorted according to HHsearch [14] score of the template used) are displayed in the Jmol window as cartoons and colored according to solvent accessibilities. For the model, the transparent solvent excluded surface is also shown. A ligand binding Isoleucine is highlighted in both structures, as well as in the most accurate model for the same protein. The Isoleucine in one of the models is predicted to be in an incorrectly modeled loop, far away from its correct position.
Mentions: The page contains a short description of the protein and a sortable table (Figure 3B) where the models are listed and can be ranked. One or more models can be visualized using a Jmol applet (Figure 3A) and are shown superimposed to the experimental structure. Different representations are possible (cartoons, spacefill, trace, backbone representations, etc.) and solvent excluded and solvent accessible surfaces can be rendered. A state win-dow records what happens in the Jmol applet (Figure 3C). The user can also rotate the axes in the Jmol window and create images.

Bottom Line: The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest.The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively.Any restrictions to use by non-academics: No.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physics, Sapienza University of Rome, P,le A, Moro, 5, 00185 Rome, Italy.

ABSTRACT

Background: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application.

Results: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively.

Conclusions: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

Show MeSH