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.pl Supplementary data are available at Bioinformatics online.