The ModFOLD Model Quality Assessment Server
About the latest server
The ModFOLD4 server provides:
- A single score and a p-value relating to the predicted quality of a single 3D model of a protein structure.
- Rankings for multiple 3D models for the same protein target according to predicted model quality.
- Predictions of the local quality (per-residue error) within multiple models.
Figure 1 taken from McGuffin (2008). The predicted per-residue error (left) for an example model is compared to the observed error obtained from the alignment to the native structure (right). Each image was rendered using Pymol (http://www.pymol.org). The colours represent the residue accuracy according to the temperature scheme (blue indicates residues closest to the native structure; red, those furthest from the native structure).
ReferencesPlease cite the following papers:
McGuffin, L. J., Buenavista, M. T., & Roche, D. B. (2013) The ModFOLD4 Server for the Quality Assessment of 3D Protein Models. Nucleic Acids Res., 41, W368-72. PubMed
The server implements the IntFOLD2-TS method to generate alternative models:
Buenavista, M. T., Roche, D. B. & McGuffin, L. J. (2012) Improvement of 3D protein models using multiple templates guided by single-template model quality assessment. Bioinformatics, 28, 1851-1857. PubMed
The server implements ModFOLDclust2 to cluster models:
McGuffin, L. J. & Roche, D. B. (2010) Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments. Bioinformatics, 26, 182-188. PubMed
- McGuffin, L. J. (2008) The ModFOLD Server for the Quality Assessment of Protein Structural Models. Bioinformatics, 24, 586-7. PubMed CASP8 paper describing the ModFOLDclust method and ModFOLD version 2.0:
- McGuffin, L. J. (2009) Prediction of global and local model quality in CASP8 using the ModFOLD server. Proteins: Structure Function and Bioinformatics, 77, 185-190. PubMed Original benchmarking of the ModFOLD method:
- McGuffin, L. J. (2007) Benchmarking consensus model quality assessment for protein fold recognition. BMC Bioinformatics, 8, 345. PubMed
Paper describing the original ModFOLD server:
- Pettitt, C. S., McGuffin, L. J. & Jones, D. T. (2005) Improving sequenced based fold recognition by use of 3D model quality assessment. Bioinformatics, 21, 3509-3515. PubMed
- Wallner, B. & Elofsson, A. (2003) Can correct protein models be identified? Protein Sci. 12, 1073-1086.
- May 2013: Improved error reporting.
- April 2013: ModFOLD4 server paper published in NAR.
- Dec 2012: ModFOLD4 server now online and open to all users
- Dec 2012: Success at CASP10: ModFOLD4 quasi-single model method among top ranked methods; talk given at Quality Assessment session.
- Aug 2012: ModFOLD 4.0 open beta version online for testing please send feedback to email@example.com
- Sept 2011: ModFOLD 3.0 now includes confidence scores (p-values).
- Oct 2010: ModFOLD version 3.0 (beta) online for testing - the method implements the multi-model methods ModFOLDclust2, ModFOLDclustQ and the single-model mode method, ModFOLD 3.0.
- Nov 2008: ModFOLD version 2.0 online for testing - the method aims to combine the ModFOLD and ModFOLDclust methods and outputs results in QMODE2 format.
- July 2008: Fair usage policy introduced due to high demand.
- March 2008: The ModFOLD servlet code has been moved to a new server for CASP8.
- Feb 2008: If models are incorrectly numbered then the server will now attempt to automatically renumber the ATOM records in each model in order to match the residue positions in the sequence.
- Jan 2008: The ModFOLD server paper has been published in Bioinformatics.
- Dec 2007: The DISOclust disorder prediction method has been intergrated into server. Click here for further info.
- Oct 2007: Version 1.1 of the ModFOLD server is now online. Two programs are now available:
- ModFOLD v1.1 - a fast true Model Quality Assessment Program (MQAP) that works for single or multiple models.
- ModFOLDclust v1.1 - a slower clustering method that works for multiple models only, but also provides per-residue local quality assessement.