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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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Density distribution of the number of decoy models produced for the 7,166 PDB chains in the input list. The majority of PDB chains have a number of decoy models between 0 and 10, the average being 17 and the maximum 206.
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Figure 1: Density distribution of the number of decoy models produced for the 7,166 PDB chains in the input list. The majority of PDB chains have a number of decoy models between 0 and 10, the average being 17 and the maximum 206.

Mentions: The average number of models per PDB chain in the database is 17, the largest number of models being 206 for [PDB:2RHE] chain A. The distribution of the number of models is shown in Figure 1, while Figure 2 shows the distribution of the average GDT-TS and standard deviation values for the models in the database.


A resource for benchmarking the usefulness of protein structure models.

Carbajo D, Tramontano A - BMC Bioinformatics (2012)

Density distribution of the number of decoy models produced for the 7,166 PDB chains in the input list. The majority of PDB chains have a number of decoy models between 0 and 10, the average being 17 and the maximum 206.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Density distribution of the number of decoy models produced for the 7,166 PDB chains in the input list. The majority of PDB chains have a number of decoy models between 0 and 10, the average being 17 and the maximum 206.
Mentions: The average number of models per PDB chain in the database is 17, the largest number of models being 206 for [PDB:2RHE] chain A. The distribution of the number of models is shown in Figure 1, while Figure 2 shows the distribution of the average GDT-TS and standard deviation values for the models in the database.

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