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FILTREST3D: discrimination of structural models using restraints from experimental data.


ABSTRACT: Automatic methods for macromolecular structure prediction (fold recognition, de novo folding and docking programs) produce large sets of alternative models. These large model sets often include many native-like structures, which are often scored as false positives. Such native-like models can be more easily identified based on data from experimental analyses used as structural restraints (e.g. identification of nearby residues by cross-linking, chemical modification, site-directed mutagenesis, deuterium exchange coupled with mass spectrometry, etc.). We present a simple server for scoring and ranking of models according to their agreement with user-defined restraints.FILTREST3D is freely available for users as a web server and standalone software at: http://filtrest3d.genesilico.pl/iamb@genesilico.plSupplementary data are available at Bioinformatics online.

SUBMITTER: Gajda MJ 

PROVIDER: S-EPMC2982159 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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FILTREST3D: discrimination of structural models using restraints from experimental data.

Gajda Michal J MJ   Tuszynska Irina I   Kaczor Marta M   Bakulina Anastasia Yu AY   Bujnicki Janusz M JM  

Bioinformatics (Oxford, England) 20101017 23


<h4>Summary</h4>Automatic methods for macromolecular structure prediction (fold recognition, de novo folding and docking programs) produce large sets of alternative models. These large model sets often include many native-like structures, which are often scored as false positives. Such native-like models can be more easily identified based on data from experimental analyses used as structural restraints (e.g. identification of nearby residues by cross-linking, chemical modification, site-directe  ...[more]

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