Summary: 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.
Availability: FILTREST3D is freely available for users as a web server and standalone software at: http://filtrest3d.genesilico.pl/
Contact: iamb@genesilico.pl
Supplementary information: Supplementary data are available at Bioinformatics online.